🤖 AI Summary
This work addresses the inherent trade-off between front-end accessibility and motion stability that often limits tracked robots in unstructured environments. To overcome this challenge, the authors propose TRASER, a novel tracked robot that uniquely integrates local compliance with global rigidity. By incorporating movable joints and coil-spring mechanisms, TRASER achieves simultaneous local flexibility and high structural stiffness, while internal mass redistribution enables coordinated control of its center of mass and overall configuration. Leveraging geometric and static models to optimize obstacle-traversal strategies, TRASER demonstrates record-breaking performance among tracked robots, surmounting obstacles up to 74%, 66%, and 59% of its body length in height across step, overhang, and trench terrains, respectively.
📝 Abstract
Tracked robots are widely used in unstructured environments; however, their obstacle traversal capability is fundamentally limited by a tradeoff between front-end reachability and locomotion stability. This study presents TRASER (Tracked Robot with Articulated Spine for Extended Reach), a reconfigurable tracked robot capable of relocating both its articulation point and internal mass. TRASER employs a tape-spring mechanism that localizes compliance to the bending region while maintaining high stiffness in the remaining body, thereby improving both front-end reachability and center-of-mass (CoM) shifting capability. Geometric and static models are developed to analyze the effects of articulation point and CoM position on step and ditch traversal performances. Experiments demonstrate step traversal, suspended-platform traversal, and ditch traversal of 74\%, 66\%, and 59\% of the robot body length, respectively. To the best of our knowledge, these results represent the highest reported obstacle traversal capabilities among tracked mobile robots.