Enabling Framework for Constant Complexity Model in Autonomous Inter-Reconfigurable Robots

Abstract

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(n3) 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. Note to Practitioners—This study aims to provide controls for combining multiple robots into a single system. The research study enables the robots in the system to vary and manipulate their physical structure and mechanism limitations. Onboard computation resources are often finite and incapable of computing for multiple functions that are actively in demand. Hence, this paper is motivated by the severe increase in computational demands common in a multi-robot centralized system. The paper has provided the technical details of the system architecture of the state machine and how it integrates with a typical navigation stack. The state-machine of the framework can be easily constructed using the SMACH package in the Robot Operating System and integrated by reconstruction of the navigation stack by providing the command velocity as an input and producing the transformed command velocity for the controls of the respective robots. The outcome of the paper provides a method of control in inter-reconfigurability and takes in a consistent amount of computational resources as the number of robots varies in utilization.