The paper proposes a fast method to solve the equilibrium problem of statically indeterminate walking and climbing robots with quasi-static locomotion and whatever number of legs and ropes connecting the robot frame to the ground. The configuration is instantaneously assigned. Legs and rope winches are imagined blocked. Due to the number of legs and ropes, the robot is a statically indeterminate system under unilateral constraints: in order to solve the system of the equilibrium equations, it is necessary to take into account the compliance of the robot and of the terrain. This can be done by non-linear analysis of a finite element model of the robot, including the ground characteristics, but this is very time consuming. The method presented in the paper seems an effective alternative. To assess its performances, the method is applied to the heavy-duty climbing robot Robo-climber with satisfactory results. The running time is low enough to allow the application for the online gait planning and for real-time control of the robot. The method will be soon used as decision support for online gait planning within the remote control system of Roboclimber.

Multi-legged multi-roped walking and climbing robots: online static equilibrium analysis

MOLFINO, REZIA;ZOPPI, MATTEO
2006

Abstract

The paper proposes a fast method to solve the equilibrium problem of statically indeterminate walking and climbing robots with quasi-static locomotion and whatever number of legs and ropes connecting the robot frame to the ground. The configuration is instantaneously assigned. Legs and rope winches are imagined blocked. Due to the number of legs and ropes, the robot is a statically indeterminate system under unilateral constraints: in order to solve the system of the equilibrium equations, it is necessary to take into account the compliance of the robot and of the terrain. This can be done by non-linear analysis of a finite element model of the robot, including the ground characteristics, but this is very time consuming. The method presented in the paper seems an effective alternative. To assess its performances, the method is applied to the heavy-duty climbing robot Robo-climber with satisfactory results. The running time is low enough to allow the application for the online gait planning and for real-time control of the robot. The method will be soon used as decision support for online gait planning within the remote control system of Roboclimber.
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11567/246237
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