Paper Info
Title
Planar bipedal locomotion control based on state discretization
Abstract
In this paper, a new control method for a planar bipedal robot, which we call Graph-based Model Predictive Control, is proposed. This method makes use of a directed graph constructed on the state space of the robot. The vertices of the directed graph are called waypoints, and they serve as intermediate target states to compose complex motions of the robot. By simply tracing the directed edges of the graph, one can achieve Model Predictive Control over the waypoint set. Such a directed graph is pre-designed and stored into the controller's memory to significantly reduce the computational effort required in real time. In addition, by constructing multiple directed graphs based on different objective functions, one can design multiple motions and switching trajectories among them in a uniform way. The proposed method is applied to variable-speed walking control of a bipedal walker on a two-dimensional plane, and its effectiveness is verified by numerical simulations.
Year
DOI
Venue
2010
10.1016/j.robot.2009.11.008
Robotics and Autonomous Systems
Keywords
Field
DocType
Bipedal locomotion,Discretization,Model predictive control,Offline computation
Discretization,Control theory,Simulation,Computer science,Model predictive control,Directed graph,Call graph,Waypoint,Robot,State space
Journal
Volume
Issue
ISSN
58
5
Robotics and Autonomous Systems
Citations 
PageRank 
References 
0
0.34
7
Authors
2
Name
Order
Citations
PageRank
Yuichi Tazaki17610.74
Jun-ichi Imura228551.71