Gen3 Ultra lightweight robot
A scalable, flexible and adaptable service robot, enabling researchers to customize it as needs evolve. The robot is built for human-robot interaction, meaning it’s not intended to automate tasks, but rather to work with people, enabling to transcend physical limitations.
Specifications
| Weight | 8.3 | kg (with vision module, no gripper) |
| Payload | 4 | kg (mid-range continuous; no gripper |
| 4.5 | kg (full-reach peak / temporary; nogripper) | |
| 1.1 | kg (full-reach continuous; no gripper) | |
| Maximum reach (fully extended) | 902 | mm (7 DoF) |
| Degrees of freedom | 7 | |
| Actuators | 3 | (small) |
| 4 | (large) | |
| Power supply voltage | 24 | VDC (nominal, 18 to 30 V) |
| Materials | Carbon fiber shell | |
| Aluminum | ||
| Communciations and control | 100 | Mbps Ethernet for real-time 1 kHz control |
| 100 | Mbps Ethernet for Vision module / expansion | |
| Sensors | current sensors (motor) | |
| temperatures (motor) | ||
| voltage | ||
| torque | ||
| position | ||
| Vision module | color and depth sensing |
Overview
The interface module on the robot allows connectivity with a wide variety of end effectors, instruments and sensors. The controller enables to connect the robot in a number of ways and is adaptable for multiple application needs. There are multiple ways of controlling the robot, including bypassing the controller for direct access to each individual actuator with closed-loop control at 1kHz.
The Gen3 robot has built-in discrete 2D and 3D sensors for vision-based applications.
The robot has a built-in functionality using ROS, MATLAB or Simulink. It has an advanced programming environment in C++ and Python. The web application connects from any desktop or mobile device, and no software installation is required.
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References
Describes how to get started, the robotics components, dimensions, specifications, and capabilities. Describes the interface module expansion, and the robot communications and network interfaces. Goes into the control features, an the Web App User Guide.
Describes what's inside the box, how to set it up, and how to control the robot arm with a gamepad.
Describes the product, it's features, and the software.
Continue Reading
People generally know which objects they call theirs and which they do not. For machines, however, changing functions of objects present an unresolved problem: A laboratory robot does not know which tool currently belongs to which worker.
Basic safety needs in the paleolithic era have largely evolved with the onset of the industrial and cognitive revolutions. We interact a little less with raw materials, and interface a little more with machines.
Pose estimation is an important step towards understanding people in images and videos with numerous applications in action understanding, human-robot interaction, surveillance, motion capture, and more.
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