This paper presents a novel design for mobile robot using particle swarm optimization (PSO) and adaptive NN control. The adaptive NN control strategy guarantees that robot with nonholonomic constraints can follow smooth trajectories. Based on this property, a PSO algorithm for path planning is proposed. The path planning generates smooth path with low computational cost to avoid obstacles, so t...

Abslract-The integration of evolutionary approaches with adaptive memory processes is emerging as a promising new area for research and practical applications. In this paper, we report our study on adding memory to the Evolutionary Planner/Navigator (EP/N), which is an adaptive planning/navigation system for mobile robots based on evolutionary computation. Preliminary results from our experimen...

The action language BC provides an elegant way of formalizing dynamic domains which involve indirect effects of actions and recursively defined fluents. In complex robot task planning domains, it may be necessary for robots to plan with incomplete information, and reason about indirect or recursive action effects. In this paper, we demonstrate how BC can be used for robot task planning to solve...

To solve the procurement conflict between supplier and manufacturer, this paper proposes a collaborative planning model and an adaptive negotiation method by integrating intelligent multi-agent technology. First, a collaborative procurement, inventory and production planning model is built using the multi-level multi-item capacitated lot sizing problem method. Then the particle swarm optimizati...

Abstract Aiming at the problems of large memory consumption, long operation time and low security traditional A * algorithm, a dynamic adaptive improved algorithm based on is proposed. Firstly, according to heuristic function proportion obstacles in map, weighting carried out shorten search time. Secondly, jump point (JPS) integrated remove number redundant points improve running speed algorith...