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Enabling Framework for Constant Complexity Model in Autonomous Inter-Reconfigurable Robots
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DOI：10.1109/TASE.2024.3421533.png)
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摘要
En 中文
In reconfigurable robotics, intra-reconfiguration enables a robot to change its functional abilities, while inter-reconfiguration manipulates the specification limits of the robot hardware. Although the versatility of inter-reconfigurable robots is desired in advanced autonomous systems, the O(n(3)) algorithm computational time complexity challenge comes when multiple modular robots combine and reconfigure into a bigger form structure for autonomous navigation tasks. This phenomenon has limited the inter-reconfiguration potential of expansion, versatility, and robustness. In this paper, a navigation framework with non-complex transformation states is proposed for inter-reconfigurable robots to perform combining and splitting control dimensions. Simulations have shown the complexity from O(n) to constant time O(1) in the reconfiguration states of the framework on a considerable number of robot agents. Additionally, a set of inter-reconfigurable robots, Wasp Biggie, was used to demonstrate the proof-of-concept in experiments as a fully functional centralized planner system. These experiments showed outperforming results on the consistent utility of CPU consumption while performing navigation and reconfiguration.
Keyword:
Reconfiguration
autonomy
navigation
inter-reconfiguration
complexity theory
finite state machine
robot frame
centralized system
autonomy
navigation
inter-reconfiguration
complexity theory
finite state machine
robot frame
centralized system
期刊
IF:
6.4
论文数:
5.2K
被引数:
1.6W
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