Learning impedance modulation for physical interaction: Insights from humans and advances in robotics
an IROS 2020 Event
October 25-29, 2020 - Las Vegas, NV, USA
At the moment, robots are mainly employed for industrial applications where accurate positioning and precise tracking are needed. This led to the development of robotic systems that were stiff and heavy. As such, they can only operate in highly structured environments void of any physical interaction with humans. This limitation has motivated the robotic research community to develop novel theoretical and technological solutions to allow robots to operate amongst and with humans and to safely move in unknown and unstructured environments. To guarantee human safety, the stability and integrity of the robot must be preserved during physical interaction. A common approach is to introduce a certain degree of compliance to the robot, which allows it to account for external disturbances. Compliance can be embedded in robots either passively or actively. For instance, passive visco-elastic elements can be integrated into the robot design. Alternatively, a controller can shape the mechanical impedance of the robot (e.g., stiffness, damping, inertia). This means robot behavior can be planned not only in the kinematic domain (i.e. motion planning) but also in terms of its dynamic response. These approaches have been proven effective in managing physical interaction with its surrounding environment and humans. Still, knowing what the desired robot compliance should be for a given scenario is an open problem. The primary goal of this full-day workshop is to critically discuss the current and new approaches used to identify the proper robot compliance for a given task, interaction, level of uncertainty, etc. We invited speakers to discuss how the selection of impedance parameters can be formulated as an optimization problem, as well as speakers who use learning strategies to understand and generalize task-specific impedance regulation. We have also invited speakers from the human motor control community to discuss how humans are able to robustly manage physical interaction by modulating their mechanical impedance.
The nature of this workshop is by definition multidisciplinary, since it leverages on human observation to tackle the problem of exploiting robotic systems for tasks (potentially) involving a high level of forceful interactions, including interactions with unknown and dynamic environments or cooperation with humans. A proper impedance regulation is indeed an aspect of paramount importance to fruitfully execute the desired task while avoiding damages to the robot and guaranteeing human safety.
• Impedance/Admittance Control
• Variable Stiffness Actuator (VSA) robots/continuum soft robots stiffness/impedance optimization
• Impedance planning
• Impedance regulation in human beings
• Impedance learning from demonstration
• Trajectory and impedance optimization/learning in robots and humans
• Physical human-robot interaction
• Impedance regulation in human and robot balancing
A selection of experts in the field will alternate in 30 mins talks (time for questions included), organized in two different sessions: (1) insights from humans physiology and control; (2) impedance regulation on robotic systems.
Posters will be selected from a call for extended abstracts, reviewed by the organizers. Those who want to participate are required to submit an extended abstract (2 pages maximum). All submissions will be reviewed using a single-blind review process. The poster contributions will first be presented as flash-talks in dedicated teaser sessions, followed by the poster presentation at the end of each session. Hands-on demos are also encouraged.
This workshop is supported by the European Union’s Horizon 2020 research and innovation programme under grant agreement No. 688857 (SoftPro), No. 810346 (Natural BionicS), No. 871237 (Sophia), No. 732737 (ILIAD) and No. 780883 (Thing). The content of this publication is the sole responsibility of the authors. The European Commission or its services cannot be held responsible for any use that may be made of the information it contains.