A stability analysis of walking robots based on leg-end supporting moments

D. Zhou , K.H. Low , Teresa Zielińska


An essential consideration in the development of any motion planning method for a multilegged vehicle is to maintain stability during walking. We propose a leg-end supporting moment (LSM) method, to measure the stability margin of walking robots. The LSM is defined as the product of the force acting on a supporting leg and the distance between the supporting leg and the opposite edge of the support polygon. These forces and distances can be obtained online from the internal robot sensors. The stability margin evaluated by the LSM method, expressed as LSMm, is defined as the quotient of the leg-end supporting moment over the weight of the robot. If the LSMm is greater than zero, the robot is in stable state. Otherwise the robot will be in marginally stable state or will lose its stability. The simulation results show that the LSM method is suitable for the stability analysis in cases with and without external forces acting on the body. The method is not only effective for flat terrain, but also for uneven terrain. These characteristics enable the LSM method to measure the stability margin of a walking robot in the case of drilling, dragging and manipulating, also in the case when the robot is used in forestry
Author D. Zhou
D. Zhou,,
, K.H. Low
K.H. Low,,
, Teresa Zielińska (FPAE / IAAM)
Teresa Zielińska,,
- The Institute of Aeronautics and Applied Mechanics
Pages2834-2839 vol.3
Publication size in sheets0.5
Book Proceedings 2000 ICRA. International Conference on Robotics and Automation, 2000, San Francisco, IEEE Robotics and Automation Society, ISBN 0-7803-5886-4, [0-78035887-2], 1051 p.
Keywords in Englishdragging, drilling, flat terrain, force feedback, Forestry, leg-end supporting moments, legged locomotion, manipulating, multilegged vehicle, path planning, position control, stability, Stability analysis, stability margin, uneven terrain, Walking robots
Languageen angielski
Score (nominal)0
Publication indicators GS Citations = 21.0
Citation count*21 (2020-08-23)
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