Please use this identifier to cite or link to this item: https://doi.org/10.1016/j.robot.2010.12.006
Title: A GJK-based approach to contact force feasibility and distribution for multi-contact robots
Authors: Zheng, Y. 
Chew, C.-M. 
Adiwahono, A.H.
Keywords: Contact force distribution
Equilibrium
GJK distance algorithm
Linear programming
Minimum norm solution
Multi-contact robots
Issue Date: Mar-2011
Citation: Zheng, Y., Chew, C.-M., Adiwahono, A.H. (2011-03). A GJK-based approach to contact force feasibility and distribution for multi-contact robots. Robotics and Autonomous Systems 59 (3-4) : 194-207. ScholarBank@NUS Repository. https://doi.org/10.1016/j.robot.2010.12.006
Abstract: This paper presents a new approach to two fundamental problems concerning the equilibrium of a multi-contact robot: the contact force feasibility (CFF) and the contact force distribution (CFD). The CFF is to determine if there exist feasible contact forces to maintain a robot in equilibrium without breaking its contacts with the environment, while the CFD is to compute the minimum contact forces if a feasible solution exists. A general measure of overall contact force magnitude is defined, which includes the traditional measure (i.e., the sum of normal force components) and a more complex measure (i.e., the maximum of normal force components) as special cases. We first reduce the two problems into verifying the existence of nonnegative solutions and determining the nonnegative minimum one-norm solution to a system of linear equations, respectively. To obtain the explicit formulation of the linear system, it is required to compute the Minkowski sum of point sets, which usually is computationally expensive. Then, based on the GJK distance algorithm, we develop an iterative algorithm, which enables us to solve the linear system without calculating the Minkowski sum and compute the CFF and CFD in real time. © 2010 Elsevier B.V. All rights reserved.
Source Title: Robotics and Autonomous Systems
URI: http://scholarbank.nus.edu.sg/handle/10635/54221
ISSN: 09218890
DOI: 10.1016/j.robot.2010.12.006
Appears in Collections:Staff Publications

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