Proceedings of the NATO advanced research workshop and EGS topical workshop on Chaotic advection, tracer dynamics and turbulent dispersion
Perception, planning, and control for autonomous walking with the Ambler planetary rover
International Journal of Robotics Research
Machines That Walk: The Adaptive Suspension Vehicle
Machines That Walk: The Adaptive Suspension Vehicle
Biologically Inspired Neural Controllers for Motor Control in a Quadruped Robot
IJCNN '00 Proceedings of the IEEE-INNS-ENNS International Joint Conference on Neural Networks (IJCNN'00)-Volume 6 - Volume 6
Adaptive Dynamic Walking of a Quadruped Robot on Natural Ground Based on Biological Concepts
International Journal of Robotics Research
Timed trajectory generation using dynamical systems: Application to a Puma arm
Robotics and Autonomous Systems
Machine learning for fast quadrupedal locomotion
AAAI'04 Proceedings of the 19th national conference on Artifical intelligence
ICRA'09 Proceedings of the 2009 IEEE international conference on Robotics and Automation
A brainstem-like modulation approach for gait transition in a quadruped robot
IROS'09 Proceedings of the 2009 IEEE/RSJ international conference on Intelligent robots and systems
Gait Pattern Based on CMAC Neural Network for Robotic Applications
Neural Processing Letters
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In this article, we propose a bio-inspired architecture for a quadruped robot that is able to initiate/stop locomotion; generate different gaits, and to easily select and switch between the different gaits according to the speed and/or the behavioral context. This improves the robot stability and smoothness while locomoting. We apply nonlinear oscillators to model Central Pattern Generators (CPGs). These generate the rhythmic locomotor movements for a quadruped robot. The generated trajectories are modulated by a tonic signal, that encodes the required activity and/or modulation. This drive signal strength is mapped onto sets of CPG parameters. By increasing the drive signal, locomotion can be elicited and velocity increased while switching to the appropriate gaits. This drive signal can be specified according to sensory information or set a priori. The system is implemented in a simulated and real AIBO robot. Results demonstrate the adequacy of the architecture to generate and modulate the required coordinated trajectories according to a velocity increase; and to smoothly and easily switch among the different motor behaviors.