Publications
128 results found
Kormushev P, Caldwell DG, 2013, Reinforcement Learning with Heterogeneous Policy Representations
Kryczka P, Hashimoto K, Takanishi A, et al., 2013, Walking Despite the Passive Compliance: Techniques for Using Conventional Pattern Generators to Control Instrinsically Compliant Humanoid Robots
Carrera A, Carreras M, Kormushev P, et al., 2013, Towards valve turning with an AUV using Learning by Demonstration
Dallali H, Mosadeghzad M, Medrano-Cerda GA, et al., 2013, Development of a dynamic simulator for a compliant humanoid robot based on a symbolic multibody approach, Pages: 598-603
Kormushev P, Calinon S, Caldwell DG, 2013, Reinforcement Learning in Robotics: Applications and Real-World Challenges, Robotics, Vol: 2, Pages: 122-148, ISSN: 2218-6581
Kryczka P, Shiguematsu YM, Kormushev P, et al., 2013, Towards dynamically consistent real-time gait pattern generation for full-size humanoid robots
Kryczka P, Kormushev P, Hashimoto K, et al., 2013, Hybrid gait pattern generator capable of rapid and dynamically consistent pattern regeneration, Publisher: IEEE, Pages: 475-480
Kormushev P, Caldwell DG, 2012, Direct policy search reinforcement learning based on particle filtering
Colasanto L, Kormushev P, Tsagarakis N, et al., 2012, Optimization of a compact model for the compliant humanoid robot COMAN using reinforcement learning, International Journal of Cybernetics and Information Technologies, Vol: 12, Pages: 76-85, ISSN: 1311-9702
COMAN is a compliant humanoid robot. The introduction of passive compliance in some of its joints affects the dynamics of the whole system. Unlike traditional stiff robots, there is a deflection of the joint angle with respect to the desired one whenever an external torque is applied. Following a bottom up approach, the dynamic equations of the joints are defined first. Then, a new model which combines the inverted pendulum approach with a three-dimensional (Cartesian) compliant model at the level of the center of mass is proposed. This compact model is based on some assumptions that reduce the complexity but at the same time affect the precision. To address this problem, additional parameters are inserted in the model equation and an optimization procedure is performed using reinforcement learning. The optimized model is experimentally validated on the COMAN robot using several ZMP-based walking gaits.
Shen H, Yosinski J, Kormushev P, et al., 2012, Learning Fast Quadruped Robot Gaits with the RL PoWER Spline Parameterization, International Journal of Cybernetics and Information Technologies, Vol: 12
Dallali H, Kormushev P, Li Z, et al., 2012, On Global Optimization of Walking Gaits for the Compliant Humanoid Robot COMAN Using Reinforcement Learning, International Journal of Cybernetics and Information Technologies, Vol: 12
Leonetti M, Kormushev P, Sagratella S, 2012, Combining Local and Global Direct Derivative-free Optimization for Reinforcement Learning, International Journal of Cybernetics and Information Technologies, Vol: 12
Carrera A, Ahmadzadeh SR, Ajoudani A, et al., 2012, Towards Autonomous Robotic Valve Turning, Cybernetics and Information Technologies, Vol: 12, Pages: 17-26
Kormushev P, Calinon S, Ugurlu B, et al., 2012, Challenges for the policy representation when applying reinforcement learning in robotics, Pages: 1-8
Kormushev P, Caldwell DG, 2012, Simultaneous discovery of multiple alternative optimal policies by reinforcement learning, Pages: 202-207
Kormushev P, Ugurlu B, Colasanto L, et al., 2012, The anatomy of a fall: Automated real-time analysis of raw force sensor data from bipedal walking robots and humans, Pages: 3706-3713
Calinon S, Kormushev P, Caldwell DG, 2012, Compliant skills acquisition and multi-optima policy search with EM-based reinforcement learning, Robotics and Autonomous Systems
Lane DM, Maurelli F, Kormushev P, et al., 2012, Persistent Autonomy: the Challenges of the PANDORA Project
Kormushev P, Ugurlu B, Calinon S, et al., 2011, Bipedal Walking Energy Minimization by Reinforcement Learning with Evolving Policy Parameterization, Pages: 318-324
Kormushev P, Ugurlu B, Calinon S, et al., 2011, Bipedal walking energy minimization by reinforcement learning with evolving policy parameterization, 2011 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2011), Publisher: IEEE
Kormushev P, Nenchev DN, Calinon S, et al., 2011, Upper-body Kinesthetic Teaching of a Free-standing Humanoid Robot, Pages: 3970-3975
Kormushev P, Nomoto K, Dong F, et al., 2011, Time Hopping Technique for Faster Reinforcement Learning in Simulations, International Journal of Cybernetics and Information Technologies, Vol: 11, Pages: 42-59
Kormushev P, Calinon S, Caldwell DG, 2011, Imitation Learning of Positional and Force Skills Demonstrated via Kinesthetic Teaching and Haptic Input, Advanced Robotics, Vol: 25, Pages: 581-603
Kormushev P, Calinon S, Saegusa R, et al., 2010, Learning the skill of archery by a humanoid robot iCub, Pages: 417-423
Kormushev P, Calinon S, Caldwell DG, 2010, Approaches for Learning Human-like Motor Skills which Require Variable Stiffness During Execution
Kormushev P, Calinon S, Caldwell DG, 2010, Robot Motor Skill Coordination with EM-based Reinforcement Learning, Pages: 3232-3237
Sato F, Nishii T, Takahashi J, et al., 2010, Whiteboard Cleaning Task Realization with HOAP-2, Pages: 426-429
Kormushev P, Nomoto K, Dong F, et al., 2009, Eligibility Propagation to Speed up Time Hopping for Reinforcement Learning, Journal of Advanced Computational Intelligence and Intelligent Informatics, Vol: 13, No. 6
Kormushev P, 2009, Time Hopping Technique for Reinforcement Learning and its Application to Robot Control
Kormushev P, Dong F, Hirota K, 2009, Probability redistribution using time hopping for reinforcement learning
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