Underactuated Legged-Rolling Locomotion of a Minimal Two-Rod Tensegrity Robot with Self-Recovery Capability
Yanqiu Zheng, Yuxuan Xiang, YUETONG HE, Fumihiko Asano, Isao T. Tokuda
AI summary
Problem
Legged robots struggle with self-recovery and efficient terrain traversal, while rolling robots lack discrete grounding points for uneven ground; combining them typically requires complex, heavy modular designs that are difficult to control.
Approach
The authors propose a control method for a minimal two-rod tensegrity robot that divides locomotion into two phases: overcoming gravitational potential barriers and adjusting posture for landing, using only four actively controlled elastic cables.
Key results
- Numerical demonstration of quasi-static and dynamic legged-rolling gaits
- Autonomous self-recovery from arbitrary stationary postures
- Physical validation of uphill climbing and stair traversal
- Clearance of discrete steps up to 20% of the robot's frame length
Why it matters
This work provides a lightweight, compliant, and highly robust locomotion paradigm for mobile robots operating in unpredictable or disaster-prone environments.
Abstract
A control method is proposed for a tensegrity robot to generate legged-rolling locomotion (i.e., rolling movement produced by a legged system). The robot has a minimal structure composed only of two rods and four elastic cables. The difficulty of the control arises from the minimalistic structure that makes the system underactuated. Our control strategy is divided into two phases: 1) overcoming the gravitational potential energy and 2) adjusting the robot’s posture to prepare for the landing. Numerical simulations demonstrated that the system was capable of traversing complex terrains with two types of gaits, i.e., quasi- static and dynamic gaits. The proposed structure also enabled the robot to autonomously recover from arbitrary stationary states and initiate legged-rolling locomotion. Physical experiments validated the applicability of the tensegrity robot to various terrains such as uphill and stair climbing and showed its capability of overcoming discrete steps up to 20 % of the robot’s frame length.