It would be awesome to have robots that can help us do important things, like aid disaster recovery efforts or monitor the environment. In the case of quadrupeds, robots that walk on four legs, their mobility requires many software components to work together seamlessly. It&rsquo;s a drag when all your time is spent on developing lower-level infrastructure instead of focusing on high-level behaviors. <a href="https://engineering.cmu.edu/directory/bios/johnson-aaron.html" id="isPasted" target="_blank">Aaron Johnson</a>&rsquo;s <a href="https://www.cmu.edu/me/robomechanicslab/" rel="noopener" target="_blank">Robomechanics Lab</a> experienced these frustrations firsthand. His team often had to rely on simple models for doing research because existing software solutions were not open sourced, did not provide a modular framework, and lacked end-to-end functionality.&nbsp;<img src="https://images.wevolver.com/eyJidWNrZXQiOiJ3ZXZvbHZlci1wcm9qZWN0LWltYWdlcyIsImtleSI6ImZyb2FsYS8xNjU5NzE4NTkzNzMxLTA3MjYtZW0tMS1xdWFkcnVwZWQucG5nIiwiZWRpdHMiOnsicmVzaXplIjp7IndpZHRoIjo5NTAsImZpdCI6ImNvdmVyIn19fQ==" style="width: 766px;" class="fr-fic fr-dib">A four-legged robot using Quad-SDK software is shown jumping. Source:&nbsp;Carnegie Mellon University/Robomechanics Lab&nbsp;An example of innovation born out of necessity, Johnson, an associate professor of <a href="https://www.meche.engineering.cmu.edu/index.html" id="isPasted" rel="noopener" target="_blank">mechanical engineering</a>, and his team designed their own locomotion software stack, <a href="https://github.com/robomechanics/quad-sdk" rel="noopener" target="_blank">Quad-SDK</a>, a full-stack framework for agile quadrupedal locomotion. Many graduate students have contributed to the development of the software across a two-year period, but it was time well spent. Their design can simplify the development process for roboticists everywhere because it uses an open-source license, meaning the software can be used and modified as the user wishes. Quad-SDK comes ready to use, so researchers don&rsquo;t have to worry about implementing the necessary tools and infrastructure; instead, they can get right to work on exciting behaviors and applications.&nbsp;<iframe src="https://www.youtube.com/embed/kSXKjTxKpuA?&wmode=opaque&rel=0&enablejsapi=1&origin=https://www.wevolver.com" frameborder="0" allowfullscreen="" class="fr-draggable" data-lf-yt-playback-inspected-kn9eq4roawkarlvp="true" style="width: 767px; height: 430px;"></iframe>Unlike other options, Quad-SDK is also compatible with the Robot Operating System (ROS). ROS is a middleware, somewhere between hardware and software, that lets different parts of a system talk to each other. For example, if a robot senses an obstacle in its path and needs to transfer information from its perception module to its decision-making module, ROS is what enables that communication. Imagine an app that doesn&rsquo;t use iOS or Android&mdash;it&rsquo;s much simpler when everything works together.Locomotion is a layered problem, as team member and Ph.D. student Ardalan Tajbakhsh describes it. &ldquo;In order to do anything meaningful on a robot, you need to have many components working together seamlessly.&rdquo; Quad-SDK provides a framework for robotics researchers and developers to focus their efforts on the core algorithms instead of the software tooling and infrastructure.<blockquote>In order to do anything meaningful on a robot, you need to have many components working together seamlessly. - Ardalan Tajbakhsh, Ph.D. student, Mechanical Engineering&nbsp;</blockquote>Other software packages are very good at solving one component, like motion planning, but it&rsquo;s critical to have end-to-end frameworks that provide the necessary algorithms, tools, and infrastructure for performing high-quality robotics research. Quad-SDK is full stack, meaning it contains every level of the hierarchy that affects quadruped locomotion, starting with global planning. This layer sits at the top of the stack; Tajbakhsh compares it to Google Maps, because it chooses where the robot should roughly go to reach its destination. The next layer, local planner, is what decides the specifics of the route, like where the robot should place its feet. This culminates in a third layer, the robot driver, which sends commands to the quadruped&rsquo;s joints to execute the desired motion.In the weeks since Quad-SDK <a href="https://leggedrobots.org/contributions.html" rel="noopener" target="_blank">won a Best Paper Award</a> at the Workshop on Legged Robots at the 2022 IEEE International Conference on Robotics and Automation (ICRA), people have already requested to use it, a clear indicator of how useful its solutions are and how the open-source format invites collaboration within the robotics community. Figuratively and literally, Quad-SDK can go many places.

Aaron Johnson’s Robomechanics Lab has developed an open-source software that enables more agile movement in legged robots.

Open-source software gives a leg up to robot research

Steep sections on slippery ground, high steps, scree and forest trails full of roots: the path up the 1,098-metre-high Mount Etzel at the southern end of Lake Zurich is peppered with numerous obstacles. But ANYmal, the quadrupedal robot from the Robotic Systems Lab at ETH Zurich, overcomes the 120 vertical metres effortlessly in a 31-minute hike. That’s 4&nbsp;minutes faster than the estimated duration for human hikers – and with no falls or missteps.This is made possible by a new control technology, which researchers at ETH Zurich led by robotics professor Marco Hutter recently presented in the journal <a target="_blank">Science Robotics</a>. “The robot has learned to combine visual perception of its environment with proprioception – its sense of touch – based on direct leg contact. This allows it to tackle rough terrain faster, more efficiently and, above all, more robustly,” Hutter says. In the future, ANYmal can be used anywhere that is too dangerous for humans or too impassable for other robots.<iframe src="https://www.youtube.com/embed/0e40Umfnl_w?&amp;wmode=opaque&amp;rel=0" frameborder="0" allowfullscreen="" class="fr-draggable" style="width: 767px; height: 431px;"></iframe>Video: Nicole Davidson / ETH Zurich&nbsp;<h2 id="isPasted">Perceiving the environment accurately</h2>To navigate difficult terrain, humans and animals quite automatically combine the visual perception of their environment with the proprioception of their legs and hands. This allows them to easily handle slippery or soft ground and move around with confidence, even when visibility is low. Until now, legged robots have been able to do this only to a limited extent.“The reason is that the information about the immediate environment recorded by laser sensors and cameras is often incomplete and ambiguous,” explains Takahiro Miki, a doctoral student in Hutter’s group and lead author of the study. For example, tall grass, shallow puddles or snow appear as insurmountable obstacles or are partially invisible, even though the robot could actually traverse them. In addition, the robot’s view can be obscured in the field by difficult lighting conditions, dust or fog.“That’s why robots like ANYmal have to be able to decide for themselves when to trust the visual perception of their environment and move forward briskly, and when it is better to proceed cautiously and with small steps,” Miki says. “And that’s the big challenge.”<h2>A virtual training camp</h2>Thanks to a new controller based on a neural network, the legged robot ANYmal, which was developed by ETH Zurich researchers and commercialized by the ETH spin-off <a href="https://www.anybotics.com/company/" target="_blank">ANYboticscall_made</a>, is now able to combine external and proprioceptive perception for the first time. Before the robot could put its capabilities to the test in the real world, the scientists exposed the system to numerous obstacles and sources of error in a virtual training camp. This let the network learn the ideal way for the robot to overcome obstacles, as well as when it can rely on environmental data – and when it would do better to ignore that data.“With this training, the robot is able to master the most difficult natural terrain without having seen it before,” says ETH Zurich Professor Hutter. This works even if the sensor data on the immediate environment is ambiguous or vague. ANYmal then plays it safe and relies on its proprioception. According to Hutter, this allows the robot to combine the best of both worlds: the speed and efficiency of external sensing and the safety of proprioceptive sensing.<h2>Use under extreme conditions</h2>Whether after an earthquake, after a nuclear disaster, or during a forest fire, robots like ANYmal can be used primarily wherever it is too dangerous for humans and where other robots cannot cope with the difficult terrain.In September of last year, ANYmal was able to demonstrate just how well the new control technology works at the <a href="https://mavt.ethz.ch/de/news-und-veranstaltungen/d-mavt-news/2021/09/siegreiche-teilnahme-an-robotik-wettbewerb.html" target="_blank">DARPA Subterranean Challenge</a>, the world’s best-known robotics competition. The ETH Zurich robot automatically and quickly overcame numerous obstacles and difficult terrain while autonomously exploring an underground system of narrow tunnels, caves, and urban infrastructure. This was a major part of why the ETH Zurich researchers, as part of the CERBERUS team, took first place with a prize of 2 million dollars.<hr><h2>Reference</h2>Miki T, Lee J, Hwangbo J, Wellhausen L: Learning robust perceptive locomotion for quadrupedal robots in the wild, Science Robotics 2022, doi: <a href="https://doi.org/10.1126/scirobotics.abk2822" target="_blank">10.1126/scirobotics.abk2822call_made</a>

The legged robot ANYmal on the rocky path to the summit of Mount Etzel, which stands 1,098 metres above sea level. (Photo: Takahiro Miki)

ETH researchers led by Marco Hutter developed a new control approach that enables a legged robot, called ANYmal, to move quickly and robustly over difficult terrain. Thanks to machine learning, the robot can combine its visual perception of the environment with its sense of touch for the first time.

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Open-source software gives a leg up to robot research

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