Enhanced Negotiation and Opportunistic Optimization for Market-Based Multirobot Coordination

Abstract Multirobot coordination, if made efficient and robust, promises high impact on automation. Thechallenge is to enable robots to work together in an intelligent manner to execute a global task. The marketapproach has had considerable success in the multirobot coordination domain. However the implementationof this approach to date restricts the negotiations to two-party, single-task deals which often forces the taskallocation solution into a local minimum. This report investigates the effects of introducing multi-party andmulti-task negotiations to enhance the market-based approach to multirobot coordination. Multi-partynegotiations are enabled by implementing a combinatorial exchange mechanism, while multi-tasknegotiations are accomplished via clustering of tasks in cost space. Presented results show that global costscan be considerably reduced (on average to within 10% of the optimal solution for the tested scenarios),and hence task allocation can be considerably improved, by enhancing the negotiation capabilities of therobots.This report also investigates the effects of introducing opportunistic optimization with leaders to enhancemarket-based multirobot coordination. Leaders are able to optimize within subgroups of robots bycollecting information about their tasks and status, and re-allocating the tasks within the subgroup in a moreprofitable manner. The presented work also considers the effects of introducing pockets of centralizedoptimization into an otherwise distributed system. The implementations were tested on a variation of thetraveling salesman problem. Presented results show that global costs can be reduced, and hence, taskallocation can be improved, utilizing leaders. Note the presented work only addresses scenarios whereleaders run exchanges to optimize task allocation within a group of robots. Some leaders are also capableof clustering tasks and hence can conduct combinatorial exchanges. But these are not the only opportunitiesfor leaders to optimize within the market. It is also possible to have combinatorial exchanges and leadersas distinct entities within the economy. Leaders could also use other approaches to generate plans for asubgroup of robots. Finally, a leader could simply act as a means of enabling trade between subgroups ofrobots who are otherwise unable to communicate, thus enriching the set of possible trades. Thus, leaderscan enhance the market-based approach by several means including optimizing task-allocation, generatingplans, optimizing plans, and enabling better trade opportunities between groups of traders.