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Abstract
This dissertation explores novel approaches for collaborative control and computational offloading strategies in multi-robot systems operating in dynamic environments. The research focuses on developing frameworks and algorithms to optimize resource utilization, enhance system efficiency, and adapt to rapidly changing network and computing conditions. Key contributions include investigating remote control and collaboration frameworks, centralized offloading strategies for sequential multi-robot tasks, decentralized consensus- based scheduling schemes for collaborative tasks, and communication-aware offloading frameworks. Through theoretical analysis, simulation studies, andreal-world experiments, the proposed methodologies demonstrate their effectiveness in improving task execution times, reducing latency, and enhancing overall system performance. The research outcomes contribute to the advancement of collaborative computational control and offer promising solutions for optimizing multi-robot system operations in dynamic and resource-constrained environments