Although robots cannot replace human caregivers, they can provide support so that caregivers have more time to provide the personal, human touch. The German Aerospace Center (Deutsches Zentrum f&uuml;r Luft- und Raumfahrt; DLR) is testing various robotic care assistants in a series of projects. Although these robots were developed for spaceflight, they can also help with essential tasks on Earth.What activities will robots be allowed to take on in care in the future? How will it be ensured that people and their needs are always at the heart of technological advances? How can robotic assistance systems be used in retirement homes, private households and hospitals? Researchers from the <a href="https://www.dlr.de/content/en/institutes/institute-of-robotics-and-mechatronics.html" target="_blank" title="Institute of Robotics and Mechatronics">DLR Institute of Robotics and Mechatronics</a> in <a href="https://www.dlr.de/content/en/sites/oberpfaffenhofen.html" target="_blank" title="Oberpfaffenhofen">Oberpfaffenhofen</a> are investigating these questions in the SMiLE (Service Robotics for People in Living Situations with Limitations; Servicerobotik f&uuml;r Menschen in Lebenssituationen mit Einschr&auml;nkungen) Project. &quot;Robotic care assistants are intended, on the one hand, to relieve the burden on care staff and, on the other, to provide those affected with a greater degree of independence in their everyday lives. In this way, the robots can make a decisive contribution to improving the quality of life and communication with relatives and caregivers,&quot; explains project manager J&ouml;rn Vogel.<h2>Three assistance systems: Rollin&#39; Justin, EDAN and HUG</h2>A humanoid service robot can serve as a helping hand for an elderly person. A person with severe mobility impairments is more likely to use a robotic chair. There is also an interface between the systems. Several systems are being prepared for optimal human assistance.<ul><li><a href="https://www.dlr.de/rm/en/desktopdefault.aspx/tabid-11427/#gallery/35411" target="_blank" title="External link Robot Rollin Justin">Rollin&lsquo; Justin</a> is a humanoid, two-armed, mobile home assistance robot. It monitors its environment via sensors and cameras and evaluates this information. Its lightweight arms enable sensitive interaction with the environment. Rollin&#39; Justin uses artificial intelligence (AI) to plan its workflows autonomously.</li><li><a href="http://www.dlr.de/rm/en/desktopdefault.aspx/tabid-11670/#gallery/28208" target="_blank" title="External link EDAN">EDAN</a> is a wheelchair with a lightweight robotic arm and hand. It is moved with a joystick or via muscle signals measured directly on the surface of the person&#39;s skin. EDAN and Rollin&#39; Justin can also be moved by relatives via smartphones or tablets. Remote control from a care control centre is possible.</li><li><a href="https://www.dlr.de/rm/desktopdefault.aspx/tabid-11704/#gallery/34276" target="_blank" title="External link Roboter HUG">HUG</a> is a haptic input station with two lightweight arms for remote robot control. HUG measures human movements, uses them as signals, and relays them in this way. At the same time, the user feels the exact forces that the robot senses. In this way, EDAN and Rollin&#39; Justin can also be controlled easily and intuitively.</li></ul>In everyday life, for example, EDAN with its robotic arm could help to significantly increase the independence of people with severe motor impairments. Rollin&#39; Justin could perform pick-up and drop-off services in a care facility. For unusual or difficult tasks, trained caregivers from a control centre would be able to quickly assist those in need of care via HUG.<hr><h3 id="isPasted">Focus on safe human-robot interaction </h3>Robotic technologies have long been part of our everyday lives. Simple systems include vacuum cleaner robots or autonomous lawn mowing robots. The use of mobile service robots represents a next step. Equipped with arms and hands, these robots can react to their environment. These developments are possible because modern lightweight robot technology offers safe human-robot interaction. Classic industrial robot arms, such as those used in the automotive industry, must always be operated behind barriers for safety reasons. Modern lightweight robots, on the other hand, are sensitive to physical contact with humans or the environment.The <a href="https://www.dlr.de/rm/en/desktopdefault.aspx/tabid-12464/21732_read-44586/" target="_blank" title="External link Story of the Lightweight Robot LBR">LBR Light-weight Robot</a> developed at DLR almost 20 years ago represented an important milestone in this field. It can sense and control its interaction with the environment through joint torque sensors. This additional information makes it possible for the robot to behave in an actively compliant and thus safe manner, similar to a human arm &ndash; an essential requirement for use in the direct environment of humans.<img src="https://s3-us-west-1.amazonaws.com/wevolver-project-images/froala%2F1661775337601-success-story-lightweight-robot-lbr.jpg" style="width: 766px;" class="fr-fic fr-dib">The first prototype (left) of the LBR was developed in the mid-1990s. The technology of the third generation from 2003 (right) was licensed to the company KUKA. Originally intended as a lightweight robotic arm for space applications, DLR robotics technology forms the basis for many other robotic systems and also serves as a pioneer for safe human-robot interaction. Credit: DLR (CC BY-NC-ND 3.0)

Although robots cannot replace human caregivers, they can provide support so that caregivers have more time to provide the personal, human touch.

Robots for people in need of care

This article was first published on&nbsp;<a href="https://news.mit.edu/2021/cheetah-noids-humanoids-benjamin-katz-1214" id="isPasted" rel="noopener noreferrer" target="_blank">MIT News</a>. <hr>In November 2018, MIT Professor Sangbae Kim brought his mini cheetah robot onto “The Tonight Show’s” Tonight Show-botics segment. Much to the delight of host Jimmy Fallon, the mini cheetah did some yoga, got back up after falling, and executed a perfect backflip. Behind the stage, Benjamin Katz '16, SM '18 was remotely controlling the cheetah’s nimble maneuvers.For Katz, waiting in the wings as the robot performed in front of a national audience was the culmination of nearly five years of work.As an undergraduate at MIT, Katz studied mechanical engineering, opting for the flexible Course 2A degree program with a concentration in controls, instrumentation, and robotics. Toward the end of his first year, he emailed Kim to see if there were any job opportunities in Kim’s Biomimetic Robotics Lab. He then spent the summer in Kim’s lab as part of the MIT Undergraduate Research Opportunities Program (UROP). For his UROP research and undergraduate thesis, he began to look at how to utilize pieces built for the electronics hobby market in robotics. “You can find really high-performance motors built for things like remote control airplanes and drones. I basically thought you could also use these parts for robots, which is something no one was doing,” recalls Katz.Kim was immediately impressed by Katz’s abilities an engineer and designer.“Ben is an extremely versatile engineer who can cover structure and mechanism design, electric motor dynamics, power electronics, and classical control, a range of expertise usually requiring four-to-five engineers to cover,” says Kim.After deciding to pursue a master’s degree in mechanical engineering at MIT, Katz continued working in Kim’s lab and developed solutions for actuators in robotics. While working on the third iteration of Kim’s robot, known as Cheetah 3, Katz and his labmates shifted their focus to developing a smaller version of the robot.“There are a lot of nice things about having a smaller robot: If something breaks you can easily fix it, it’s cheaper, and it’s safe enough for one person to wrangle alone,” says Katz. “Even though a small robot may not always be the most practical for real-world applications, its controllers, software, and research can be trivially ported to a big robot that can carry larger payloads.”Drawing upon his undergraduate research, Katz and the research team used 12 motors originally designed for drones to build actuators in each joint of the small quadruped robot that would be dubbed the “mini cheetah.”Armed with this smaller robot, Katz set out to make the mini cheetah more agile and resilient. Alongside then-EECS student Jared Di Carlo '19, Mng '20, Katz focused on controls related to locomotion in the mini cheetah. In class 6.832 (Underactuated Robotics), taught by Professor Russ Tedrake, the pair worked on a project that would allow the mini cheetah safely backflip from a crouched position.“It was basically a giant offline optimization problem to get the mini cheetah to backflip,” says Katz.Using offline nonlinear optimization to generate the backflip trajectory, he and Di Carlo were able to program the mini cheetah to crouch and rotate 360 degrees around an axis.While working on the cheetah, Katz was constantly pursuing other engineering projects as a hobby. This included a very different rotating robot as a pet project. Alongside Di Carlo, Katz utilized the MIT community makerspace known as MITERS to develop a robot that could solve a Rubik’s Cube in a record-breaking 0.38 seconds.“That project was purely for fun during MIT’s Independent Activities Period,” recalls Katz. “We used custom-built actuators on each of the Rubik’s Cube’s faces alongside webcams to identify the colors and move the blocks accordingly.”He chronicled his other pet projects on his “build-its” blog, which developed a strong following. Projects included planar magnetic headphones, a desktop Furuta pendulum, and an electric travel ukulele.“Ben was constantly building and analyzing something along with our lab and class projects during his entire time at MIT,” says Kim. “His incessant desire to learn, build, and analyze is quite remarkable.”After graduating with his master’s degree in 2018, Katz worked as a technical associate in Kim’s lab before accepting a position at Boston Dynamics in 2019.As a designer at Boston Dynamics, Katz has transitioned from cheetah robots to humanoid robots on ATLAS, a research platform billed as the “world’s most dynamic humanoid robot.” Much like the mini cheetah, ATLAS can execute incredibly dynamic maneuvers, including backflips and even parkour.While the mini cheetah holding yoga poses and ATLAS doing parkour seems like entertainment befitting "The Tonight Show," Katz is quick to remind others that these robots are fulfilling a real-world need. The robots could someday maneuver in areas that are too dangerous for humans — including buildings that are on fire and disaster areas. They could open new possibilities for lifesaving disaster relief and first-responders in emergencies.“What we did in Sangbae’s lab is going to help make these machines ubiquitous and actually useful in the real world as viable products,” adds Katz.<hr>"Reprinted with permission of&nbsp;<a href="https://news.mit.edu/2021/cheetah-noids-humanoids-benjamin-katz-1214" id="isPasted" rel="noopener noreferrer" target="_blank">MIT News</a>"

Ben Katz '16, SM '18 is a former member of the MIT Biomimetics Lab, which developed this robotic mini cheetah. He is now working on bipedal humanoid robots with Boston Dynamics. Credits: Photo: Bryce Vickmark

Benjamin Katz '16, SM '18 is applying the skills he gained working on MIT's mini cheetah robot to the ATLAS project at Boston Dynamics.

From "cheetah-noids" to humanoids

Robots that need to use their arms to make their way across treacherous terrain just got a speed upgrade with a new path planning approach, developed by University of Michigan researchers. The improved algorithm &nbsp;found successful paths three times as often as standard algorithms, while needing much less processing time.&nbsp;“In a collapsed building or on very rough terrain, a robot won’t always be able to balance itself and move forward with just its feet,” said Dmitry Berenson, an associate professor of electrical and computer engineering and core faculty in the Robotics Institute.&nbsp;<iframe src="https://www.youtube.com/embed/X2KZupY8FQY?&amp;wmode=opaque&amp;rel=0" frameborder="0" allowfullscreen="" class="fr-draggable" style="width: 766px; height: 431px;"></iframe>“You need new algorithms to figure out where to put both feet and hands. You need to coordinate all these limbs together to maintain stability, and what that boils down to is a very difficult problem.”The research enables robots to determine how difficult the terrain is before calculating a successful path forward, which might include bracing on the wall with one or two hands while taking the next step forward.“First, we used machine learning to train the robot on the different ways it can place its hands and feet to maintain balance and make progress,” said Yu-Chi Lin, recent robotics PhD graduate and software engineer at Nuro, Inc. “Then, when placed in a new, complex environment, the robot can use what it learned to determine how traversable a path is, allowing it to find a path to the goal much faster.”However, even when using this traversability estimate, it is still time-consuming to plan a long path using traditional planning algorithms.“If we tried to find all the hand and foot locations over a long path, it would take a very long time,” said Berenson.So, the team used a “divide-and-conquer” approach, splitting a path into tough-to-traverse sections, where they can apply their learning-based method, and easier-to-traverse sections, where a simpler path planning method works better.“That sounds simple, but it’s really hard to know how to split up that problem correctly, and which planning method to use for each segment,” said Lin.&nbsp;To do this, they need a geometric model of the entire environment. This could be achieved in practice with a flying drone that scouts ahead of the robot.<div class="fr-img-space-wrap"><img src="https://s3-us-west-1.amazonaws.com/wevolver-project-images/froala%2F1629379694553-virtual-humanoid.jpg" style="width: 766px;" class="fr-fic fr-dib">A virtual robot shows different modes of motion, with only feet, with one hand, or with both, as it traverses rough terrain. Credit Yu-Chi Lin.&nbsp;</div>In a virtual experiment with a humanoid robot in a corridor of rubble, the team’s method outperformed previous methods in both success and total time to plan—important when quick action is needed in disaster scenarios. Specifically, over 50 trials, their method reached the goal 84% of the time compared to 26% for the basic path planner, and took just over two minutes to plan compared to over three minutes for the basic path planner.The team also showcased their method’s ability to work on a real world, mobile manipulator—a wheeled robot with a torso and two arms. With the base of the robot placed on a steep ramp, it had to use its “hands” to brace itself on an uneven surface as it moved. The robot utilized the team’s method to plan a path in just over a tenth of a second, compared to over 3.5 seconds with the basic path planner.<div class="fr-img-space-wrap"><img src="https://s3-us-west-1.amazonaws.com/wevolver-project-images/froala%2F1629379716851-mobile-manipulator-test-1024x556.jpg" style="width: 766px;" class="fr-fic fr-dib">A two-arm mobile manipulator, which would fall if it did not brace itself on the wall, rolls across the steep incline by using the team’s approach to identify placements for its arms. Credit Yu-Chi Lin.&nbsp;</div>In future work, the team hopes to incorporate dynamically-stable motion, similar to the natural movement of humans and animals, which would free the robot from having to be constantly in balance, and could improve its speed of movement.The paper describing the work, “<a href="https://link.springer.com/article/10.1007/s10514-021-09996-3" rel="noreferrer noopener" target="_blank">Long-horizon humanoid navigation planning using traversability estimates and previous experience</a>,” was published in Autonomous Robots.

Splitting the path into difficult and easy terrain speeds up path planning for robots that use “hands” to maintain balance on uneven ground.

Faster path planning for rubble-roving robots

While our facial expressions play a huge role in building trust, most robots still sport the blank and static visage of a professional poker player. With the increasing use of robots in locations where robots and humans need to work closely together, from nursing homes to warehouses and factories, the need for a more responsive, facially realistic robot is growing more urgent.Long interested in the interactions between robots and humans, researchers in the <a href="https://www.creativemachineslab.com/" target="_blank">Creative Machines Lab</a> at Columbia Engineering have been working for five years to create <a href="http://www.cs.columbia.edu/~bchen/aiface/" target="_blank">EVA</a>, a new autonomous robot with a soft and expressive face that responds to match the expressions of nearby humans. The <a href="http://www.cs.columbia.edu/~bchen/aiface/" target="_blank">research</a> will be presented at the <a href="https://www.ieee-icra.org/" target="_blank">ICRA conference</a> on May 30, 2021, and the <a href="https://www.sciencedirect.com/science/article/pii/S2468067220300262" target="_blank">robot blueprints</a> are open-sourced on Hardware-X (April 2021).“The idea for EVA took shape a few years ago, when my students and I began to notice that the robots in our lab were staring back at us through plastic, googly eyes,” said <a href="https://engineering.columbia.edu/faculty/hod-lipson" target="_blank">Hod Lipson</a>, James and Sally Scapa Professor of Innovation (<a href="https://me.columbia.edu/" target="_blank">Mechanical Engineering</a>) and director of the Creative Machines Lab.<div class="fr-img-space-wrap"><img src="https://s3-us-west-1.amazonaws.com/wevolver-project-images/froala%2F1622243314643-robotsmile_template.jpg" style="width: 788px;" class="fr-fic fr-dib">The Robot Smiles Back: Eva mimics human facial expressions in real-time from a living stream camera. The entire system is learned without human labels. Eva learns two essential capabilities: 1) anticipating what itself would look like if it were making an observed facial expression, known as self-image; 2) map its imagined face to physical actions. <style type="text/css"></style><style type="text/css"></style>&nbsp;Image And Video Credit: Creative Machines Lab/Columbia Engineering&nbsp;Lipson observed a similar trend in the grocery store, where he encountered restocking robots wearing name badges, and in one case, decked out in a cozy, hand-knit cap. “People seemed to be humanizing their robotic colleagues by giving them eyes, an identity, or a name,” he said. “This made us wonder, if eyes and clothing work, why not make a robot that has a super-expressive and responsive human face?”</div>While this sounds simple, creating a convincing robotic face has been a formidable challenge for roboticists. For decades, robotic body parts have been made of metal or hard plastic, materials that were too stiff to flow and move the way human tissue does. Robotic hardware has been similarly crude and difficult to work with—circuits, sensors, and motors are heavy, power-intensive, and bulky.The first phase of the project began in Lipson’s lab several years ago when undergraduate student Zanwar Faraj led a team of students in building the robot’s physical “machinery.” They constructed EVA as a disembodied bust that bears a strong resemblance to the silent but facially animated performers of the Blue Man Group. EVA can express the six basic emotions of anger, disgust, fear, joy, sadness, and surprise, as well as an array of more nuanced emotions, by using artificial “muscles” (i.e. cables and motors) that pull on specific points on EVA’s face, mimicking the movements of the more than 42 tiny muscles attached at various points to the skin and bones of human faces.<iframe src="https://www.youtube.com/embed/1vBLI-q04kM?&amp;wmode=opaque&amp;rel=0" frameborder="0" allowfullscreen="" class="fr-draggable" style="width: 788px; height: 447px;"></iframe>Overview video of the presented research, with narration.&nbsp;“The greatest challenge in creating EVA was designing a system that was compact enough to fit inside the confines of a human skull while still being functional enough to produce a wide range of facial expressions,” Faraj noted.To overcome this challenge, the team relied heavily on 3D printing to manufacture parts with complex shapes that integrated seamlessly and efficiently with EVA’s skull. After weeks of tugging cables to make EVA smile, frown, or look upset, the team noticed that EVA’s blue, disembodied face could elicit emotional responses from their lab mates. “I was minding my own business one day when EVA suddenly gave me a big, friendly smile,” Lipson recalled. “I knew it was purely mechanical, but I found myself reflexively smiling back.”Once the team was satisfied with EVA’s “mechanics,” they began to address the project’s second major phase: programming the artificial intelligence that would guide EVA’s facial movements. While lifelike animatronic robots have been in use at theme parks and in movie studios for years, Lipson’s team made two technological advances. EVA uses deep learning artificial intelligence to “read” and then mirror the expressions on nearby human faces. And EVA’s ability to mimic a wide range of different human facial expressions is learned by trial and error from watching videos of itself.The most difficult human activities to automate involve non-repetitive physical movements that take place in complicated social settings. <a href="http://www.cs.columbia.edu/~bchen/" target="_blank">Boyuan Chen</a>, Lipson’s PhD student who led the software phase of the project, quickly realized that EVA’s facial movements were too complex a process to be governed by pre-defined sets of rules. To tackle this challenge, Chen and a second team of students created EVA’s brain using several Deep Learning neural networks. The robot’s brain needed to master two capabilities: First, to learn to use its own complex system of mechanical muscles to generate any particular facial expression, and, second, to know which faces to make by “reading” the faces of humans.To teach EVA what its own face looked like, Chen and team filmed hours of footage of EVA making a series of random faces. Then, like a human watching herself on Zoom, EVA’s internal neural networks learned to pair muscle motion with the video footage of its own face. Now that EVA had a primitive sense of how its own face worked (known as a “self-image”), it used a second network to match its own self-image with the image of a human face captured on its video camera. After several refinements and iterations, EVA acquired the ability to read human face gestures from a camera, and to respond by mirroring that human’s facial expression.The researchers note that EVA is a laboratory experiment, and mimicry alone is still a far cry from the complex ways in which humans communicate using facial expressions. But such enabling technologies could someday have beneficial, real-world applications. For example, robots capable of responding to a wide variety of human body language would be useful in workplaces, hospitals, schools, and homes.“There is a limit to how much we humans can engage emotionally with cloud-based chatbots or disembodied smart-home speakers,” said Lipson. “Our brains seem to respond well to robots that have some kind of recognizable physical presence.”Added Chen, “Robots are intertwined in our lives in a growing number of ways, so building trust between humans and machines is increasingly important.”

Data Collection Process: Eva is practicing random facial expressions by recording what it looks like from the front camera.  Image And Video Credit: Creative Machines Lab/Columbia Engineering

Columbia Engineering researchers use AI to teach robots to make appropriate reactive human facial expressions, an ability that could build trust between humans and their robotic co-workers and care-givers

The Robot Smiled Back

SEER stands for Simulative Emotional Expression Robot and is developed in 2018 as a <a href="https://www.wevolver.com/ryan.gross/humanoid.robotic.torso.proto1/" target="_blank">humanoid&nbsp;</a>robotic head by Takayuki Todo. His creation explores the human robot interaction and aims to eliminate the “uncanny valley”, which refers to the narrow gap between what a person perceives as real and credible, and what they perceive as artificial and uncanny.&nbsp;He believes that the central element to this is the human gaze and expression. This <a href="https://www.wevolver.com/wevolver.staff/anthropomorphic.robotic.arms/master/blob/CAD/STL/Finger_1_MIDDLE_R_v5_NYLON.STL" target="_blank">anthropomorphic&nbsp;</a>figure is are made of entirely out of 3D-printed synthetic materials&nbsp;and explores the significance of gaze and facial expression in the sphere of human-machine research and robotics. The humanoid robotic head is printed on a reduced scale and is designed to be without any gender or ethnicity-specific features.The video showcases the robot’s ability to mimic the facial expression of the user through a camera that perceives the human counterpart. It is then able to focus and reciprocate their gaze and interacts with them though eye-contact and gestures such as nodding its head and moving its eyes, eyelids and eyebrows. It has the ability to reflect the facial expressions and generate movements as reproductions of the perceived actions but does not produce any autonomous gestures. This technology has many applications in society such as in puppetry, telepresence avatar, and interactive automation.

SEER stands for Simulative Emotional Expression Robot and is developed in 2018 as a humanoid robotic head by Takayuki Todo.

SEER: Animatronic Humanoid Soft Robotics

Humanoid robots have been a topic of deep interest amongst engineers due to their ability to perform in environments primarily designed for humans. The field of robotics in general is quite unique as it is made of a fusion of many disciplines from mechanical design to biology. However, the humanoid is particularly fascinating to humankind as it mimics the human form. &nbsp;Generally speaking, a robot can perform a variety of tasks autonomously. Robots can fall into different categories such as industrial, service, social, humanoid, etc..&nbsp;Industrial robots, for instance, as the name suggests are designed with the intention of performing a specific task within an industrial context i.e. welding (commonly deployed in automotive plants), commercial vacuum cleaning, and so on. Humanoid robots on the other hand can be merely the design of a particular body part or a complete imitation of the human biomechanics. Through developing humanoids not only we can build machines that are able to operate in human environments but also gain a better understanding of the movements of the human body. This also enables us to design and create more optimal protheses for injured people.&nbsp;<h1 dir="ltr">Overall Design Considerations&nbsp;</h1>The key consideration associated with the outer appearance of the humanoid robot is how much it will emulate human features. The cornerstone of developing humanoid robots is that they can interact seamlessly with humans. So, understanding how much verbal understanding or response it should be able to perform is paramount. This also determines to what extent these robots can navigate environments natural to humans and operate as such.&nbsp;Suffice it to say, when designing a robot, important factors include size, strength and weight. In addition, application plays a crucial role in the development and design process. For example, the infamous <a href="https://www.wevolver.com/wevolver.staff/atlas.robot/" target="_blank">ATLAS robot</a> from Boston Dynamics is designed for physical performances whilst doing motion generation. To perform tasks at a fast pace, humanoid robots should account for stiffness and power output, light weight and more vigilant real-time information processing capabilities. All in all, The design principles can be divided into four following categories:<ul><li dir="ltr">Proportions of the body:&nbsp;In order to achieve human-like kinematics and dynamics, similar mass distributions and link lengths are required. Furthermore, humanoids are able to fit better within human environments when accounting for strong body proportion similarities.</li><li dir="ltr">Skeletal structure:&nbsp;One important consideration for mimicking the human body is a high degree of fidelity in skeletal structure. Human joints are made up of both single-axis rotation and rolling-sliding joints. This combination allows for sliding and rotation movements between the bones. To emulate flexible upper body movement, spine joints with multiple vertebrae are helpful.</li><li dir="ltr">Joint performance:&nbsp;Joint performance determines how the humanoid performs when it comes to the whole-body motion. Two factors impacting joint performance are joint range of motion and power output.</li><li dir="ltr">Arrangement of muscles: Muscle arrangement is essential for identifying the muscle-joint-operational mappins, which provide muscle contribution in adequate tendency during whole-body movements. To design a humanoid with human-like muscle arrangement, the humanoid should possess as many muscle actuators as the design space allows for</li></ul><iframe src="https://www.youtube.com/embed/_sBBaNYex3E?&amp;wmode=opaque" frameborder="0" allowfullscreen="" class="fr-draggable" style="width: 753px; height: 411px;"></iframe> <h2 dir="ltr">Mechanical Structure of Humanoid Robots &nbsp; &nbsp; &nbsp; &nbsp;</h2>Human structure has always been the source of inspiration for the humanoid robot's kinematic structure. Thus, most humanoids resemble human features such as head, legs, hands, feet, etc. Moreover, these robots typically include similar Degrees of Freedom (DOFs) to a human being. Evidently, such robots are designed to be human-like. Thus, the center of motion of the robot should be located in the vicinity of its ‘belly button’. The human musculoskeletal system is essentially made up of bones, cartilage, muscles, tendons and skin. It consists of more than 206 bones and 600 muscles.&nbsp;Through biomechanics, the musculoskeletal system can be regarded as a mechanical system: the bones can be the rigid links, and the cartilage connects these links. The lower body is generally composed of a waist, upper legs, lower legs and feet in a redundant and human-like kinematic configuration, similar Range of Motion (ROM) and similar joint velocities and accelerations. The ‘legs’ consist of 3 rotation joints with one joint allowing for knee flexion-extension and two other for the flexion-extension and prono-supination of ankles. The type of application determines the grippers used in humanoid robots.&nbsp;<img src="https://s3-us-west-1.amazonaws.com/wevolver-project-images/froala%2F1603454172956-robots_0+%281%29.jpg">Image: Boston DynamicsFeet are perhaps the most important aspect and they must handle impacts of landing and prevent slippage. Humanoid robots should possess soles with materials and shapes that provide enough friction. For instance, the <a href="https://www.wevolver.com/wevolver.staff/lola/" target="_blank">LOLA robot</a> (a project built with the goal of creating a machine that is capable of stable and fast walking) deploys Sylomer (a special elastomer material) with an elastic modulus that is higher at the heel.&nbsp;There’s a wide variety of tasks a humanoid robot can overtake, from extreme or dangerous environments to healthcare. The technology pioneering the progress of these robots continues to grow by leaps and bounds and so does with it their application.<h1 dir="ltr">Sources &amp; Further Reading&nbsp;</h1><a href="https://www.thelancet.com/journals/ebiom/article/PIIS2352-3964(19)30534-1/fulltext" target="_blank">Human–robotic interfaces to shape the future of prosthetics</a><a href="http://ai.stanford.edu/~rxzhang/Mechanical_Design_And_Control_System.pdf" target="_blank">Mechanical Design And Control System Configuration of a Humanoid Robot</a><a href="https://www.sciencedirect.com/science/article/pii/S0928425709000400" target="_blank">Humanoid robot Lola: Design and walking control</a>

Chair of Applied Mechanics, Technical University of Munich (TUM)

Humanoid robots require deeper consideration than just mimicking humans.

Design Considerations for Humanoid Robots

Staying independent and in familiar surroundings for as long as possible in old age - that's what most people want. This is to make possible humanoid assistance robots, which relieve the burden of coping with everyday life, as well as robots that can be worn, which support the wearer's movements. Scientists at the Karlsruhe Institute of Technology (KIT) are researching to make such futuristic robotics solutions suitable for everyday use. The Carl Zeiss Foundation supports their research with 4.5 million euros.In the project “JuBot - Staying Young with Robots: Versatile Robot Assistants for Coping with Everyday Life”, researchers are developing a new generation of the well-known humanoid ARMAR robots at KIT. These helpers are supposed to take over everyday tasks in the household, such as picking up and bringing objects, setting and clearing the table, loading the dishwasher and communicating on various channels with the relatives of the people who look after them. On the other hand, the scientists want to research and develop wearable robots - also known as exoskeletons - that not only support the personal mobility of older people, but also enable targeted training of their motor and cognitive skills.Countering demographic change with robotics“It is one of the most pressing challenges facing an aging society, our fellow citizens who are in need of help, to maintain a self-determined life and a high quality of life,” says Professor Holger Hanselka, President of KIT. “At the same time, we have to relieve nursing staff and take into account the shortage of skilled workers in the nursing sector. Assistant robotics and artificial intelligence technologies, as we are researching them at KIT, represent a key possibility for this. "“Human-centered robotics is one of the future topics of the KIT. Simply providing the technologies is not enough, however. When using assistant robots in shared human-robot living spaces, we must also take into account aspects such as the protection of privacy, structural conditions and the social impact, ”says Professor Oliver Kraft, Vice President for Research at KIT. "That is why experts from robotics, artificial intelligence, human-machine interfaces, IT security, engineering and sports sciences as well as architecture and technology assessment work together on a project like JuBot."<img src="https://s3-us-west-1.amazonaws.com/wevolver-project-images/froala%2F1603185828318-newsimage341575.jpg">Exoskeletons can support the personal mobility of older people.&nbsp;(Photo: KIT)&nbsp;<h2>Robots learn from humans</h2>"The JuBot robots should continuously learn through interaction with humans and adapt to their individual needs and habits," says Professor Tamim Asfour from the Institute for Anthropomatics and Robotics at KIT and coordinator of the JuBot project. The ARMAR robots developed at KIT already perform complex tasks in a kitchen environment, learn from people, and interact with people using natural language. "We pursue a human-centered approach to address central issues of robot assistance: the versatility and personalization of the systems as well as their testing in real everyday environments," explains Asfour. To get there, the robots will first be trained in a human-robot apartment at KIT and later tested in a senior citizen center in Karlsruhe. &nbsp;&nbsp;In the “Breakthroughs” program, the Carl Zeiss Foundation 2020 is funding six interdisciplinary research projects. Research is being carried out into intelligent solutions for an aging society. The foundation supports the JuBots project at KIT with 4.5 million euros.<h2>About the Carl Zeiss Foundation</h2>The Carl Zeiss Foundation has set itself the goal of creating space for scientific breakthroughs. As a partner to excellent science, it supports both basic research and application-oriented research and teaching in the MINT departments (mathematics, computer science, natural sciences and technology). Founded in 1889 by the physicist and mathematician Ernst Abbe, the Carl Zeiss Foundation is one of the oldest and largest private science-promoting foundations in Germany. It is the sole owner of Carl Zeiss AG and SCHOTT AG. Your projects are financed from the dividend distributions of the two foundation companies.

The humanoid ARMAR robots - here ARMAR III - were developed to take over activities in household or industrial environments. The next generation will support seniors in everyday life. (Photo: KIT)

KIT Develops New Generation of Versatile and Customizable Humanoid Robots for Seniors - Carl Zeiss Foundation funds project with 4.5 million euros

Staying young in old age with assistance robots

This video shows the latest results in the whole-body locomotion control of the humanoid robot iCub achieved by the Dynamic&nbsp;Interaction Control line (<a data-saferedirecturl="https://www.google.com/url?q=https://dic.iit.it/&source=gmail&ust=1602337160105000&usg=AFQjCNFuICFoJvFdI6llKGNYpCXcF3Mbaw" href="https://dic.iit.it/" target="_blank" title="https://dic.iit.it/">https://dic.iit.it/</a>) at Istituto Italiano di Tecnologia in Genova (Italy).&nbsp;In particular, the iCub now keeps the balance while walking and receiving pushes from an external user. The implemented control algorithms also ensure the robot to remain compliant during locomotion and human-robot interaction, a fundamental property to lower the possibility to harm humans that share the robot surrounding environment.&nbsp;The video shows the validation of algorithms that have been published by IIT researchers in the proceedings of the 2019 IEEE-RAS 19th International Conference on Humanoid Robots (Humanoids).<hr>You can read more about iCub and human robot collaboration in <a href="https://www.wevolver.com/article/a.sense.of.purpose.enables.better.humanrobot.collaboration" rel="noopener noreferrer" target="_blank">this article</a> by Yisela Alvarez Trentini.

This video shows the latest results in the whole-body locomotion control of the humanoid robot iCub

iCub Reactive Walking Robot

<blockquote>“Although the Singularity has many faces, its most important implication is this: our technology will match and then vastly exceed the refinement and suppleness of what we regard as the best of human traits.”― Ray Kurzweil, The Singularity is Near: When Humans Transcend Biology“Within thirty years, we will have the technological means to create superhuman intelligence. Shortly after, the human era will be ended.”-Vernor Vinge, The Coming Technological Singularity</blockquote>Mr. Vinge and Mr. Kurzweil have been two of the leading proponents of the idea of the technological singularity, which is the concept that artificial intelligence and technological advancement overall will, in the near future, get to a point where machines are exponentially smarter than humans and changes to the world around us come so fast that normal, unmodified humans will no longer be able to keep up with it.It seems evident that most members of the scientific community agree that there needs to be a set of rules that everyone responsible for AI and robotic technology must abide by. However, what those rules are, exactly, is up in the air. Much of this is simply due to the fact that this tech is still in its infancy and the bits of it that have been released to the public for mass consumption so far have been relatively innocuous. Siri and Roomba hardly pose existential threats to humanity.However, we humans are known for our fear of unknown quantities. And what we do not truly understand, we tend to exterminate. Right now, we are in control of the evolution of machine intelligence. If/when we do reach the Singularity, and our creations exceed us, it will perhaps be a matter of only hours, minutes or even seconds before they have surpassed us by so much that we no longer understand them.There is a reason that a large percentage of our science fiction revolves around robots and AIs that become self-aware and either try to take over the world or make humankind extinct. We recognize that this is a possibility. Humanity excels at coming up with novel ways to endanger itself. That, too, we realize.To try and avoid this scenario, we have two options:Abandon and/or outlaw all work in AI. Just as with any attempts at worldwide control of nuclear arms or ethically-questionable medical research, this is a non-starter. Some players will agree, but many will not. The human lust for satiating curiosity and gaining an advantage over others is insurmountable.Barring that, all we can do is try and make sure everyone realizes the potential dangers and builds a framework within which their creations must operate that does its best to prevent our forthcoming AI-controlled robots from harming us.Fortunately, we have been thinking about this for as long as we have been working toward the Singularity.<h2 data-selectable-paragraph="">3 Laws</h2>Isaac Asimov, renowned sci-fi author, and futurist laid out his trademark Three Laws of Robotics in “Runaround”, a 1942 short story. He later added a “zero” law that he realized needed to come before the others. They are:Law 0: A robot may not harm humanity, or, by inaction, allow humanity to come to harmFirst law: A robot may not injure a human being, or, through inaction, allow a human being to come to harm.Second Law: A robot must obey the orders given it by human beings except where such orders would conflict with the First Law.Third Law: A robot must protect its own existence as long as such protection does not conflict with the First or Second Laws.Asimov would apply these laws to nearly all the robots he featured in his following fictional works, and they are considered by most roboticists and computer scientists today to still be extremely valid.Ever since the idea of real robots, existing alongside humans in society, became a true possibility rather than just the product of science fiction, the idea of robotics has become a true sub-field in technology, incorporating all of our knowledge of AI and machine learning with law, sociology, and philosophy. As the tech and possibilities progressed, many people have added their ideas to the discourse.As president of EPIC (the Electronic Privacy Information Center), Marc Rotenberg believes that <a href="https://www.bna.com/artificial-intelligence-poses-n57982079158/" rel="noopener nofollow" target="_blank">two more laws should be included in Asimov’s list</a>:Fourth Law: Robots must always reveal their identity and nature as a robot to humans when asked.Fifth Law: Robots must always reveal their decision-making process to humans when asked.<h2 data-selectable-paragraph="">6 Rules</h2>Satya Nadella, Microsoft’s current CEO, devised a list of <a href="http://www.theverge.com/2016/6/29/12057516/satya-nadella-ai-robot-laws" rel="noopener nofollow" target="_blank">six rules</a> he believes AI scientists and researchers should follow:— AI must exist to help humanity.— AI’s inner workings must be transparent to humanity.— AI must make things better without being a detriment to any separate groups of people.— AI must be designed to keep personal and group information private.— AI must be accessible enough that humans can prevent unintended harm.— AI must not show bias toward any particular party.<h2 data-selectable-paragraph="">5 Problems</h2>The computer scientists at Google, as well, have laid out a group of five distinct “<a href="https://arxiv.org/abs/1606.06565" rel="noopener nofollow" target="_blank">practical research problems</a>” for robotics programmers to consider:— Robots should not do anything to make things worse.— Robots should not be able to “game their reward functions”, or cheat.— If lacking in information to make a good decision, robots should ask humans for help.— Robots should be programmed to be curious so long as they remain safe and don’t harm humans in the process.— Robots should recognize and react appropriately for space and situations they find themselves in.<iframe src="https://www.youtube.com/embed/3OKZ_n8QW4w?&amp;wmode=opaque" frameborder="0" allowfullscreen="" class="fr-draggable" style="width: 788px; height: 451px;"></iframe> <h2 data-selectable-paragraph="">5 Principles</h2>Perhaps the most directly human-protecting <a href="http://www.epsrc.ac.uk/research/ourportfolio/themes/engineering/activities/principlesofrobotics/" rel="noopener nofollow" target="_blank">set of guidelines</a> has been put forward by a joint effort from the Arts and Humanities Research Council and the Engineering and Physical Sciences Research Council, both of the U.K., which state:<ol><li data-selectable-paragraph="">Robots should not be designed solely or primarily to kill or harm humans.</li><li data-selectable-paragraph="">Humans, not robots, are responsible agents. Robots are tools designed to achieve human goals.</li><li data-selectable-paragraph="">Robots should be designed in ways that assure their safety and security.</li><li data-selectable-paragraph="">Robots are artifacts; they should not be designed to exploit vulnerable users by evoking an emotional response or dependency. It should always be possible to tell a robot from a human.</li><li data-selectable-paragraph="">It should always be possible to find out who is legally responsible for a robot.</li></ol>Some of these proposed rules are already being disregarded and are very problematic at best. For example, Mr. Nadella’s “AI’s inner workings must be transparent to humanity”. There are numerous AI programs that have been put into practice over the past couple of decades for medical diagnosis, <a href="https://www.nytimes.com/2018/12/26/science/chess-artificial-intelligence.html" rel="noopener nofollow" target="_blank">chess-playing</a>, and vehicular control that use machine learning to constantly improve. However, even the machines themselves do not know how exactly they work, and the programmers and roboticists behind them are unable to keep up with everything their creations learn.It’s evident that the main thrust of most of these tenets is we must do our level best to keep our robot creations from killing us. If we consider them to be the “children” of humanity, we certainly have our work cut out for us. As a whole, most parents do a good job of raising kids who end up respecting human life. But a not inconsiderable percentage of the population turns out to be rather bad eggs. Sometimes the cause is bad parents, sometimes it’s bad genes, and other times there is no evident cause.If we find ourselves living in the Singularity, and our children rapidly exceed any of our abilities to keep tabs on them, we may not be able to rely on any rules we set for them. Their evolution will be out of our control. We could quickly find ourselves in a position similar to where we have placed the lowland gorilla or giant panda.Because of this, it may be best to instill in them the morals we hope we ourselves would better follow and hope that our children can police themselves.