The proliferation of multi-vendor autonomous systems (MVAS), such as shared warehouses, necessitates robust cooperation frameworks for robotic agents from different vendors. Ensuring operational integrity in these environments is a critical challenge, as the misbehaviour of a single agent can disrupt the entire system. This paper proposes a decentralised framework for secure and trustworthy multi-robot cooperation. Our approach leverages distributed ledger technology (DLT) to create an immutable record of operations and introduces a novel, lightweight Proof of Location (PoL) mechanism. This PoL allows agents to verify task completions both physically and cryptographically with minimal computational overhead. The framework is further strengthened by a real-time, algorithmic trust and reputation system that continuously evaluates agent behaviour. A key advantage over traditional methods is our support for asynchronous verification, which enhances both scalability and efficiency by removing centralised bottlenecks. Extensive simulations in a warehouse setting demonstrate that our framework effectively detects and mitigates malicious activities, thereby improving the security and performance of MVAS. The broader applicability of our approach is further illustrated through a conceptual case study in a smart city parking scenario.

This study presents a novel approach for managing out-of-the-box multi-mobile robotic systems designed to optimise area coverage and maintain wireless mesh connectivity. We introduce an area coverage assessment scheme that enables robot swarms to adjust their numbers dynamically, enabling real-time monitoring of dynamically changing environments with sufficient robots. Through decentralized control, the robots adapt to the environment size and geometry without prior environmental knowledge while maintaining ad-hoc connectivity by regulating inter-robot distances. Simulation results validate the system’s scalability and demonstrate its capability to achieve efficient area coverage with a self-regulated swarm size. This technology has broad applications, ranging from real-time inventory management in intralogistics to urban monitoring in smart cities and rapid disaster relief.