Multi-robot exploration mission planning and stochastic increment replanning for load balance

Abstract

Multi-robot mission planning is composed of assignment allocation and mobile-robot route planning in this paper. Multi-robot exploration missions adopts fuzzy c-mean (FCM) algorithm to allocate, and then, heterogeneous interactive cultural hybrid algorithm (HICHA) is devised for route planning in order to optimize mobilerobot execution path. Meanwhile, we design multi-robot mission replanning mechanism based on the rules system of greedy algorithm for dynamic stochastic increment missions. Finally, extensive simulation experiments were shown that FCM for assignment allocation and HICHA for route planning were efficacious for mobile-robot exploration mission planning. Furthermore, the improved greedy algorithm based on experience rules met dynamic stochastic increment missions replanning requirement for load balance.

A cost-effective planning method for automatic measurement based on task similarity and octopus optimization

“…This kind of problem is common in the electricity, storage, logistics, and space detection industries, etc., and recent research has focussed on multiprocessor systems, robots, drones, and satellite formation-flying systems [20][21][22][23][24]. Yu [25] adopted a fuzzy c-mean algorithm to allocate robots. Crosby [26] presented a two-level mission-planning method, and a multi-agent planning algorithm was introduced to find reduced makespan plans for a multi-robot problem.…”