Learning Collaborative Impedance-Based Robot Behaviors

Research in learning from demonstration has focused on transferring movements from humans to robots. However, a need is arising for robots that do not just replicate the task on their own, but that also interact with humans in a safe and natural way to accomplish tasks cooperatively. Robots with variable impedance capabilities opens the door to new challenging applications, where the learning algorithms must be extended by encapsulating force and vision information. In this paper we propose a framework to transfer impedance-based behaviors to a torque-controlled robot by kinesthetic teaching. The proposed model encodes the examples as a task-parameterized statistical dynamical system, where the robot impedance is shaped by estimating virtual stiffness matrices from the set of demonstrations. A collaborative assembly task is used as testbed. The results show that the model can be used to modify the robot impedance along task execution to facilitate the collaboration, by triggering stiff and compliant behaviors in an on-line manner to adapt to the user's actions.

[1]  Neville Hogan,et al.  Impedance Control: An Approach to Manipulation , 1984, 1984 American Control Conference.

[2]  N. Hogan,et al.  Impedance Control:An Approach to Manipulation,Parts I,II,III , 1985 .

[3]  N. Higham.  COMPUTING A NEAREST SYMMETRIC POSITIVE SEMIDEFINITE MATRIX , 1988 .

[4]  Mitsuo Kawato,et al.  Equilibrium-Point Control Hypothesis Examined by Measured Arm Stiffness During Multijoint Movement , 1996, Science.

[5]  Aaron F. Bobick,et al.  Parametric Hidden Markov Models for Gesture Recognition , 1999, IEEE Trans. Pattern Anal. Mach. Intell..

[6]  Rieko Osu,et al.  The central nervous system stabilizes unstable dynamics by learning optimal impedance , 2001, Nature.

[7]  Inna Sharf,et al.  Contact Stiffness and Damping Estimation for Robotic Systems , 2003, Int. J. Robotics Res..

[8]  Brian Rooks.  The harmonious robot , 2006, Ind. Robot.

[9]  Alin Albu-Schäffer,et al.  The DLR lightweight robot: design and control concepts for robots in human environments , 2007, Ind. Robot.

[10]  Kyle B. Reed,et al.  Physical Collaboration of Human-Human and Human-Robot Teams , 2008, IEEE Transactions on Haptics.

[11]  Stefan Schaal,et al.  Robot Programming by Demonstration , 2009, Springer Handbook of Robotics.

[12]  Paul Evrard,et al.  Learning collaborative manipulation tasks by demonstration using a haptic interface , 2009, ICAR.

[13]  Paul Evrard,et al.  Homotopy switching model for dyad haptic interaction in physical collaborative tasks , 2009, World Haptics 2009 - Third Joint EuroHaptics conference and Symposium on Haptic Interfaces for Virtual Environment and Teleoperator Systems.

[14]  Henk Nijmeijer,et al.  Robot Programming by Demonstration , 2010, SIMPAR.

[15]  Darwin G. Caldwell,et al.  Learning-based control strategy for safe human-robot interaction exploiting task and robot redundancies , 2010, 2010 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[16]  Alin Albu-Schäffer,et al.  Biomimetic motor behavior for simultaneous adaptation of force, impedance and trajectory in interaction tasks , 2010, 2010 IEEE International Conference on Robotics and Automation.

[17]  Carme Torras,et al.  Sharpening haptic inputs for teaching a manipulation skill to a robot , 2010 .

[18]  Alessandro De Luca,et al.  Residual-based stiffness estimation in robots with flexible transmissions , 2011, 2011 IEEE International Conference on Robotics and Automation.

[19]  Abderrahmane Kheddar,et al.  Motion learning and adaptive impedance for robot control during physical interaction with humans , 2011, 2011 IEEE International Conference on Robotics and Automation.

[20]  Dongheui Lee,et al.  Incremental kinesthetic teaching of motion primitives using the motion refinement tube , 2011, Auton. Robots.

[21]  Stefan Schaal,et al.  Learning force control policies for compliant manipulation , 2011, 2011 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[22]  Weihua Sheng,et al.  Using human motion estimation for human-robot cooperative manipulation , 2011, 2011 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[23]  Nikolaos G. Tsagarakis,et al.  Statistical dynamical systems for skills acquisition in humanoids , 2012, 2012 12th IEEE-RAS International Conference on Humanoid Robots (Humanoids 2012).

[24]  Aude Billard,et al.  Online learning of varying stiffness through physical human-robot interaction , 2012, 2012 IEEE International Conference on Robotics and Automation.

[25]  Siddhartha S. Srinivasa,et al.  Learning the communication of intent prior to physical collaboration , 2012, 2012 IEEE RO-MAN: The 21st IEEE International Symposium on Robot and Human Interactive Communication.

[26]  Carme Torras,et al.  A robot learning from demonstration framework to perform force-based manipulation tasks , 2013, Intelligent Service Robotics.

[27]  Angelika Peer,et al.  The Role of Haptic Feedback for the Integration of Intentions in Shared Task Execution , 2013, IEEE Transactions on Haptics.

[28]  Bilge Mutlu,et al.  Coordination Mechanisms in Human-Robot Collaboration , 2013 .

[29]  G. Schreiber,et al.  The Fast Research Interface for the KUKA Lightweight Robot , 2022 .