Abstract
To this day, despite the increasing motor capability of robotic devices, elaborating efficient control strategies is still a key challenge in the field of humanoid robotic arms. In particular, providing a human “pilot” with efficient ways to drive such a robotic arm requires thorough testing prior to integration into a finished system. Additionally, when it is needed to preserve anatomical consistency between pilot and robot, such testing requires to employ devices showing human-like features. To fulfill this need for a biomimetic test platform, we present Reachy, a human-like life-scale robotic arm with seven joints from shoulder to wrist. Although Reachy does not include a poly-articulated hand and is therefore more suitable for studying reaching than manipulation, a robotic hand prototype from available third-party projects could be integrated to it. Its 3D-printed structure and off-the-shelf actuators make it inexpensive relatively to the price of an industrial-grade robot. Using an open-source architecture, its design makes it broadly connectable and customizable, so it can be integrated into many applications. To illustrate how Reachy can connect to external devices, this paper presents several proofs of concept where it is operated with various control strategies, such as tele-operation or gaze-driven control. In this way, Reachy can help researchers to explore, develop and test innovative control strategies and interfaces on a human-like robot.
Highlights
While robotic systems keep improving in terms of motor capabilities thanks to progress in mechatronics, developing control strategies and interfaces allowing a human to harness the full potential of an advanced robotic arm proves to be a key challenge in the field of humanoid robotics and in particular, rehabilitation engineering
We present Reachy, a life-size test platform to be used by researchers to explore, develop, and test control strategies and interfaces for human-driven robotics
4http://creativecommons.org/licenses/by-sa/4.0/ 5http://cad.onshape.com/documents/66388ae9c63cef53d76acd77/w/ 68c2411483d5bc65c7f54234/e/581d46ba9b8ee98de9d636ee 6http://gnu.org/licenses/lgpl-3.0.html 7http://github.com/pollen-robotics/reachy 8http://gnu.org/licenses/gpl.html 9http://github.com/poppy-project/pypot 10http://github.com/poppy-project a cost function, attributing a scalar value to any set of angles to quantify to what extent it is a good solution with respect to the Inverse Kinematics (IK) problem: a lower cost means a better solution
Summary
While robotic systems keep improving in terms of motor capabilities thanks to progress in mechatronics, developing control strategies and interfaces allowing a human to harness the full potential of an advanced robotic arm proves to be a key challenge in the field of humanoid robotics and in particular, rehabilitation engineering. Even in the case of an ablebodied human, the gap between robotic devices’ complexity and available command signals highlights the need for efficient and usable control interfaces and strategies To bridge this gap, researchers have investigated techniques to retrieve additional input data from the human. Other works investigated how Augmented Reality (AR) can be employed to provide relevant visual feedback about a robotic arm’s state (Markovic et al, 2014, 2017), with the aim of improving the control loop Another approach to overcome this limit is to reduce the need for command signals, by making the robotic system take charge of part of its own complexity. Even though its use cases are not limited to this field, this robotic platform is primarily intended for applications in prosthetics and rehabilitation engineering
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