Legged robots that balance
Perception, planning, and control for autonomous walking with the Ambler planetary rover
International Journal of Robotics Research
Omnidirectional Locomotion for Quadruped Robots
RoboCup 2001: Robot Soccer World Cup V
Texture Synthesis by Non-Parametric Sampling
ICCV '99 Proceedings of the International Conference on Computer Vision-Volume 2 - Volume 2
Adaptive Dynamic Walking of a Quadruped Robot on Natural Ground Based on Biological Concepts
International Journal of Robotics Research
Machine learning for fast quadrupedal locomotion
AAAI'04 Proceedings of the 19th national conference on Artifical intelligence
The Stanford LittleDog: A learning and rapid replanning approach to quadruped locomotion
International Journal of Robotics Research
Supporting locomotive functions of a six-legged walking robot
International Journal of Applied Mathematics and Computer Science - SPECIAL SECTION: Efficient Resource Management for Grid-Enabled Applications
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Legged robots offer the potential to navigate highly challenging terrain, and there has recently been much progress in this area. However, a great deal of this recent work has operated under the assumption that either the robot has complete knowledge of its environment or that its environment is suitably regular so as to be navigated with only minimal perception, an unrealistic assumption in many real-world domains. In this paper we present an integrated perception and control system for a quadruped robot that allows it to perceive and traverse previously unseen, rugged terrain that includes large, irregular obstacles. A key element of the system is a novel terrain modeling algorithm, used for filling in the occluded models resulting from on-board vision systems. We apply our approach to the LittleDog robot, and show that it allows the robot to walk over challenging terrain using only on-board perception.