Deep Learning And Unsupervised Feature Learning
CONTRIBUTED BY
Andrew Ng
J.Zico Kolter
Pieter Abbeel
Yirong Shen
Honglak Lee
Sam Schreiber
Youngjun Kim
Mike Rodgers

Description

Legged robots, unlike wheeled robots, have the potential to access nearly all of the earth's land mass, enabling robotic applications in areas where they are currently infeasible. However, the current control software for legged robots is quite limited, and does not let them realize this potential. In the Learning Locomotion project, we seek to develop software that significantly advances the state of the art in robotic quadruped locomotion over rough terrain. To achieve this goal, we develop and apply novel control and machine learning algorithms. We gratefully acknowledge DARPA for supporting this work.

Publications

Stereo Vision and Terrain Modeling for Quadruped Robots J. Zico Kolter, Youngjun Kim, and Andrew Y. Ng. To appear in Proceedings of the IEEE International Conference on Robotics and Automation, 2009.[pdf]

Task-Space Trajectories via Cubic Spline Optimization J. Zico Kolter and Andrew Y. Ng. To appear in Proceedings of the IEEE International Conference on Robotics and Automation, 2009. [pdf]

A Control Architecture for Quadruped Locomotion over Rough Terrain J. Zico Kolter, Mike P. Rodgers, and Andrew Y. Ng. In Proceedings of the IEEE International Conference on Robotics and Automation, 2008.[pdf]

Hierarchical Apprenticeship Learning with Application to Quadruped Locomotion J. Zico Kolter, Pieter Abbeel, and Andrew Y. Ng. In Neural Information Processing Systems, 2007.[pdf]

Learning Omnidirectional Path Following Using Dimensionality Reduction J. Zico Kolter and Andrew Y. Ng. In Proceedings of Robtics: Science and Systems, 2007.[pdf]

Quadruped Robot Obstacle Negotiation via Reinforcement Learning Honglak Lee, Yirong Shen, Chih-Han Yu, Gurjeet Singh, and Andrew Y. Ng. In Proceedings of the IEEE International Conference on Robotics and Automation , 2006.[pdf]

Video Links

Dynamic Jumping Manuever
Crossing Terrains of Increasing Difficulty
Planning Before/After Learning #1
Dynamic Jumping Manuever
Planning Before/After Learning #2
Omnidirectional Path Following
Learning to Balance

O2O VIDEOS


Related Projects

Leave a Reply

You must be logged in to post a comment