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Conference Papers Year : 2021

Modeling and Optimal Control for Rope-Assisted Rappelling Maneuvers

Abstract

Envisioning the employment of rope-assisted humanoid robots to reduce human intervention for operations in the heights, this work addresses the modeling and motion planning problems for a rope-assisted bipedal robot. The mathematical features of this system outnumber the ones of typical humanoid robots, including: under-actuation of the floating-base joints, the rope pulling effect and the passive connection between the robot body and the rope master-point. These characteristics render the study of a rope-assisted bipedal robot both fascinating and unexplored, raising motion planning challenges when attempting to plan dynamic suspended maneuvers, as rappelling. To this end, we first introduce a template three-mass model of a bipedal robot connected trough passive joints to an extensible rope, which is in turn modeled as a two-mass body. Based on this, a family of optimal control problems is presented to plan different rappelling maneuvers.
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Dates and versions

hal-03157675 , version 1 (03-03-2021)

Identifiers

Cite

Enrico Mingo Hoffman, Matteo Parigi Polverini, Arturo Laurenzi, Nikos G Tsagarakis. Modeling and Optimal Control for Rope-Assisted Rappelling Maneuvers. 2021 IEEE International Conference on Robotics and Automation (ICRA), May 2021, Xi'an, China. pp.9826-9832, ⟨10.1109/ICRA48506.2021.9560802⟩. ⟨hal-03157675⟩
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