Intelligent Rock-Climbing Robot Capable of Multimodal Locomotion and Hybrid Bioinspired Attachment.

Abstract

Rock-climbing robots have significant potential in fieldwork and planetary exploration. However, they currently face limitations such as a lack of stability and adaptability on extreme terrains, slow locomotion, and single functionality. This study introduces a novel multimodal and adaptive rock-climbing robot (MARCBot), which addresses these limitations through spiny grippers that draw inspiration from morpho-functionalities observed in beetles, arboreal birds, and hoofed animals. This hybrid bioinspired design enables high attachment strength, passive adaptability to different terrains, and quick attachment on rock surfaces. The multimodal functionality of the gripper allows for attachment during climbing and support during walking. A novel control strategy using dynamics and quadratic programming (QP) optimizes attachment wrench distribution, reducing cost-of-transport by 20.03% and 6.05% compared to closed-loop inverse kinematic (CLIK) and virtual model control (VMC) methods, respectively. MARCBot achieved climbing speeds of 0.15mmin-1 on a vertical discrete rock surface under gravity and trotting speeds of up to 0.21ms-1 on various complex terrains. It is the first robot capable of climbing on rock surfaces and trotting in complex terrains without the need for switching end-effectors. This study highlights significant advancements in climbing and multimodal locomotion for robots in extreme environments.