Cooperative Motion Generation Using Nonlinear Model Predictive Control for Heterogeneous Agents in Warehouse

摘要

In this work, we propose a model predictive control to generate cooperative motion of heterogeneous agents which operate in a limited area such as warehouses, considering optimization of entire performance of the area and collision avoidance constraints. In the proposed method, we can comprehensively optimize the motion of the heterogeneous agents by constructing an objective function and a dynamical model integrating the state and input of all agents, and considering the constraints to be satisfied with a single agent and combination of agents based on the specification of each agent such as size and actuator limitations. Furthermore, using a map data represented as an occupancy grid map, collision avoidance is realized not only between agents, but also between agents and arbitrary shape obstacles in the target area. The effectiveness of the proposed method is verified in a numerical simulation in which heterogeneous mobile robots with heterogeneous characteristics operate in a warehouse model.