Legged locomotion is one of the most important but also one of the hardest control
problems in humanoid robotics and none of the current approaches completely solves it to date. As it is obvious from studies of humans and animals, learning plays a significant role in both the balance stabilization and gait generation of biological legged creatures. It is therefore both an important application as well as an essential problem for learning control.
Our approaches to learning control for locomotion are highly intertwined with both our work in learning and control in the other research on this website. Previously developed learning and control techniques provide us with a unique framework and allow us to create novel approaches to locomotion. For example, motor primitives for gaits and foot placement can become essential tools. Such motor primitives can be learned using a mixture of imitation learning and reinforcement learning. Their execution as well as the balancing of the robot are hard nonlinear control problems which can be solved by few control laws including learning control laws developed in our lab.
We study locomotion mainly using two systems, i.e., the humanoid robot
Computational Brain CB and the quadruped robot Little Dog. The humanoid robot CB is one of the most advanced humanoid robots and is driven using hydraulic actuators. Developed by SARCOS Inc., it is located at our collaborator's facility at ATR, Kyoto, Japan and shown in the the picture above. The quadruped robot Little Dog is special platform for learning locomotion developed by Boston Dynamics Inc. One Little Dog is located at the University of Southern California in Los Angeles, CA and shown at the right. The Little Dog project has started in Fall 2005 and is part of the DARPA Learning Locomotion program.
Contact persons: Jun Nakanishi, Michael Mistry, Jan Peters, Dimitris Pongas, Stefan Schaal
Kalakrishnan, M.; Buchli, J.; Pastor, P.; Schaal, S. (2009). Learning Locomotion over Rough Terrain using Terrain Templates, IEEE/RSJ International Conference on Intelligent RObots and Systems.
[Keywords: quadruped locomotion, learning from demonstration]
[Detail] [BibTeX] [PDF]
Buchli, J.; Kalakrishnan, M.; Mistry, M.; Pastor, P.; Schaal, S. (2009). Compliant Quadruped Locomotion Over Rough Terrain, IEEE/RSJ International Conference on Intelligent RObots and Systems.
[Keywords: quadruped locomotion, inverse dynamics, force control]
[Detail] [BibTeX] [PDF]
Mistry, M.;Nakanishi, J.;Schaal, S. (2007). Task space control with prioritization for balance and locomotion, IEEE International Conference on Intelligent Robotics Systems (IROS 2007).
[Keywords: operational space control, locomotion, balance, hierarchical]
[Detail] [BibTeX] [PDF]
Pongas, D.;Mistry, M.;Schaal, S. (2007). A robust quadruped walking gait for traversing rough terrain, International Conference on Robotics and Automation (ICRA2007), pp.1474-1479.
[Keywords: quadruped locomotion, static walk, crawl gait, cog trajectory, rough terrain, internal-model control]
[Detail] [BibTeX] [PDF]
Nakanishi, J.;Morimoto, J.;Endo, G.;Cheng, G.;Schaal, S.;Kawato, M. (2004). Learning from demonstration and adaptation of biped locomotion, Robotics and Autonomous Systems, 47, 2-3, pp.79-91.
[Keywords: movement primitives, locomotion, phase resetting, learning from demonstration]
[Detail] [BibTeX] [PDF]
Nakanishi, J.;Morimoto, J.;Endo, G.;Cheng, G.;Schaal, S.;Kawato, M. (2004). A framework for learning biped locomotion with dynamic movement primitives, IEEE-RAS/RSJ International Conference on Humanoid Robots (Humanoids 2004), IEEE.
[Keywords: movement primitives, dynamic systems, locomotion, phase resetting, learning]
[Detail] [BibTeX] [PDF]
Schaal, S.;Peters, J.;Nakanishi, J.;Ijspeert, A. (2004). Learning Movement Primitives, International Symposium on Robotics Research (ISRR2003), Springer.
[Keywords: movement primitives, supervised learning, reinforcment learning, locomotion, phase resetting, learning from demonstration]
[Detail] [BibTeX] [PDF]
Nakanishi, J.;Morimoto, J.;Endo, G.;Schaal, S.;Kawato, M. (2003). Learning from demonstration and adaptation of biped locomotion with dynamical movement primitives, Workshop on Robot Learning by Demonstration, IEEE International Conference on Intelligent Robots and Systems (IROS 2003).
[Keywords: movement primitives, locomotion, phase resetting, learning from demonstration]
[Detail] [BibTeX] [PDF]
Schaal, S.;Peters, J.;Nakanishi, J.;Ijspeert, A. (2003). Control, planning, learning, and imitation with dynamic movement primitives, Workshop on Bilateral Paradigms on Humans and Humanoids, IEEE International Conference on Intelligent Robots and Systems (IROS 2003).
[Keywords: movement primitives, supervised learning, reinforcment learning, locomotion, phase resetting, learning from demonstration]
[Detail] [BibTeX] [PDF]
Nakanishi, J.;Fukuda, T.;Koditschek, D. E. (2000). A brachiating robot controller, IEEE Transactions on Robotics and Automation, 16, 2, pp.109-123.
[Keywords: dynamic systems, nonlinear robot control, brachiation, dynamically dexterous robotics, limit cycles, locomotion, swing map, symmetry, target dynamics, task encoding, underactuated system.]
[Detail] [BibTeX] [PDF]
The pictures on this web page are here due to the courtesy of SARCOS, ATR, Boston Dynamics and the Department of Defense.