Sha Yi, Shashwat Singh, Allison Seo, Ryan St. Pierre, Katia Sycara, Zeynep Temel
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Reconfigurable robot swarms for terrain traversal with passive coupling mechanisms
In biological swarms, army ants and bees have demonstrated the ability to form functional structures for collaborative tasks. Achieving similar functionality with robot swarms requires forming connections between robots using electrical, magnetic, or mechanical means. Our research introduces the PuzzleBots–robot swarms equipped with passive coupling mechanisms that enable collective behavior. These mechanisms leverage the individual mobility and dexterity of each robot to achieve complex assemblies. By coupling together, PuzzleBots can form both rigid and flexible structures that significantly enhance their ability to navigate challenging terrains. Rigid structures offer high load-bearing and transportation capabilities, while flexible structures provide compliance with environmental geometries. We demonstrated that these assembled structures can be precisely controlled using our distributed Model Predictive Control framework. Our results show that passive coupling in robot swarms significantly improves the traversal capability on rough and discontinuous terrains compared with individual robots.
期刊介绍:
Autonomous Robots reports on the theory and applications of robotic systems capable of some degree of self-sufficiency. It features papers that include performance data on actual robots in the real world. Coverage includes: control of autonomous robots · real-time vision · autonomous wheeled and tracked vehicles · legged vehicles · computational architectures for autonomous systems · distributed architectures for learning, control and adaptation · studies of autonomous robot systems · sensor fusion · theory of autonomous systems · terrain mapping and recognition · self-calibration and self-repair for robots · self-reproducing intelligent structures · genetic algorithms as models for robot development.
The focus is on the ability to move and be self-sufficient, not on whether the system is an imitation of biology. Of course, biological models for robotic systems are of major interest to the journal since living systems are prototypes for autonomous behavior.