Precise Motion Control for Self-Reconfiguration Wave-Like Crawling Robots in Parallel Connection With Limited Resources

Mobile robots face significant challenges in traditional fixed structure limitations, particularly in complex terrains and tasks. To solve the above-mentioned problem, self-reconfiguration wave-like crawling (SWC) robots are designed to perform complex tasks efficiently through physical connections and move across various surfaces. In addition, the parallel connection is designed to facilitate differential steering and enhance the robot's load-bearing capacity. Since autonomous robots have limited resources, including computation, communication, and energy, reducing resource usage to the fullest extent possible is crucial while maintaining control performance. Therefore, a precise motion controller is proposed for SWC robots in parallel connection. Specifically, the kinematic model of the SWC robots in parallel connection is established and transformed into a trajectory-tracking error model. Then, a continuous-time optimal motion control law is designed to achieve stable trajectory-tracking with reduced control energy. In addition, a self-triggered mechanism is introduced with a significant advancement in reducing sensor sampling and saving resource costs. These merits are validated through an IoT-based (Internet of Things) self-built hardware experimental platform, demonstrating a significant resource-saving potential over traditional periodic control methods.