A Decentralized Approach to Cooperative Situation Assessment in Multi-Robot Systems

Abstract

To act effectively under uncertainty, multi-robot teams need to accurately estimate the state of the environment. Although individual robots, with uncertain sensors, may not be able to accurately determine the current situation, the team as a whole should have the capability to perform situation assessment. However, sharing all information with all other team mates is not scalable nor is centralization of all information possible. This paper presents a decentralized approach to cooperative situation assessment that balances use of communication bandwidth with the need for good situation assessment. When a robot believes locally that a particular plan should be executed, it sends a proposal for that plan, to one of its team mates. The robot receiving the plan proposal, can either agree with the plan and forward it on, or it can provide sensor information to suggest that an alternative plan might have higher expected utility. Once sufficient robots agree with the proposal, the plan is initiated. The algorithm successfully balances the value of cooperative sensing against the cost of sharing large volumes of information. Experiments verify the utility of the approach, showing that the algorithm dramatically out-performs individual decision-making and obtains performance similar to a centralized approach

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