AI & ML
Linear Twisting Sidewinding Gaits for Twistable Snake Robot Motion Planning on Complex Terrains
arXiv cs.RO0 views
arXiv:2610.29461v1 Announce Type: new Abstract: Sidewinding is an efficient gait for snake robots to locomote on various terrains, by undulating the backbone curve and shifting the contact segments along it. However, relying solely on undulatory motion limits the locomotive capability of snake robots, and combining it with twisting motion can improve their speed and robustness. This hypothesis has recently been verified by the rolling vector approach, which locomotes the robot like a differential-drive car. Yet its twisting is concentrated in a short buffer segment, imposing most of the workload on the two twist joints in the middle, which can often overburden the motors and limit its locomotion. With that in mind, this paper develops a new family of twisting sidewinding gaits that distribute the workload over the entire body with our proposed linear twisting function. Under matched turning speed and total output power, our gaits reduce the peak output power of a single twist joint by 42%. Real-robot experiments show that, with the reduced workload, our new gaits can locomote the robot in various terrains that the existing rolling vector approach cannot. Besides, our new gaits can move up to 49% faster than conventional sidewinding without twisting.
Source:https://arxiv.org/abs/2610.29461PreviousDistance Field Driven Reinforcement Learning for Reactive and Robust Collision AvoidanceNextS-Rolling: Steerable Rolling Gaits for Twistable Snake Robots in Low-Clearance Environments
Related posts
Heated mirror reveals hidden 3D patterns in rising air near a wall
0Phys.org Tech
Infrared-transparent aerogel boosts performance of subambient daytime radiative cooling materials by up to 5.2°C
0Phys.org Tech
Tracing the online networks behind AI-generated nude images
0Phys.org Tech
Microsoft's AI Risk Report Misses This Key Detail
0Dark Reading
Introducing the Grid Protectors Program
0OpenAI Blog
The world has a new plan to save nature, but it still needs the money
0Ars Technica