MRI/Acq.: Acq. of Mobile Robot Systems for Autonomous Multiple-Cooperative Control Research Project Proposed: This project, acquiring networked mobile robotic systems, aims to advance research on cooperative motion planning and control of multiple heterogeneous mobile robots to be used in the Robotics and Embedded Systems Research Lab (RESRL) in this undergraduate institution. Implementation of energy-efficient and biologically motivated algorithms for cooperative motion planning and control enables the development of a reliable networked autonomous mobile robot system capable of operating in partially known, changing, and unpredictable environments. The work focuses on analysis and design of theoretically provable cooperative control laws for networked nonlinear dynamic systems. Currently, few results are available for cooperative control of truly nonlinear dynamic systems such as nonholonomic robots. Thus, this project involves the design of a robust, locally optimal hierarchical cooperative control strategy for networked nonholonomic constraints and obstacles avoidance issues. The development and implementation in software and in hardware of the algorithms addresses the following relevant fundamental issues. - Trajectory generation for multiple mobile robots with kinematic nonholonomic constraints, - Optimal trajectory tracking with modeling uncertainties in friction and actuator saturation, and - Less restrictive biologically-motivated local cooperative control algorithms which enable collision avoidance among robots and with obstacles in dynamic and unpredictable environments. Lyapunov argument and M-matrix theory are employed for rigorous proof of multi-robot system stability resulting from derived cooperative control algorithms. Experimental validations of the technical solutions are planned. These tests address realistic difficulties, such as wheel slippage, friction, actuators saturations, sensor and measurement noise, and communication delays adding knowledge of useful guidelines to the design and applications The research and expected results should have immediate applications in industry for factory automation, transportation, intelligent highway systems, large scale sensor networks for environmental sampling, and cooperative search and information acquisition in hazardous environments.
Broader Impacts: This project enhances collaborative multidisciplinary research between computer engineering, computer science, and environmental science. Around 120 students across those programs will be involved and trained in this undergraduate HBCU college. Research will also be disseminated by workshops and conferences.
