Route planning and scheduling system and method for multiple robots

Abstract

The invention discloses a route planning and scheduling system for multiple robots. The system comprises the multiple robots, a route environment planning unit and a scheduling unit, wherein a main control unit and an algorithm unit are arranged on each robot; the route environment planning unit is used for fragmenting all travel routes, forming network structure information and updating the information in real time; the scheduling unit issues a walking task to each main control unit and collects state information of all the robots; each main control unit plans an optimal route of the corresponding robot; each algorithm unit controls walking or obstacle avoidance according to the corresponding optimal route and relevant outside environment information; and all the routes are scored according to scoring rules for optimal route planning. The route planning and scheduling system aims at collaborative unified scheduling among the multiple robots in the system, the walking environment is predicted in advance by updating the state information of all the robots and road condition information in real time, optimization is performed continuously, blockage is avoided, the robots can walk more smoothly and more flexibly, and the purpose of system self-learning is achieved.

Description

technical field [0001] The invention relates to the field of robot control systems, in particular to a system and method for path planning and dispatching of multiple robots. Background technique [0002] At present, with the maturity of sensing technology and automatic control technology, domestic robots have been able to realize the traditional walking mode in an environment where the environment is basically determined, that is, by solidifying the preset path on the robot, the robot can walk automatically and It can realize real-time obstacle avoidance according to the scene environment. However, these walking methods cannot be predicted in advance, especially when the walking environment changes. For example, when there are multiple robots in the walking environment, it is easy for multiple robots to fail to avoid obstacles in narrow road conditions and get stuck on the same road. For an overall system composed of multiple robots, it is difficult to reasonably choose th...

AI Technical Summary

Problems solved by technology

However, these walking methods cannot be predicted in advance, especially when the walking environment changes. For example, when there are multiple robots in the walking environment, it is easy for multiple robots to fail to avoid obstacles in narrow road conditions and get stuck on the same road. For an overall system composed of multiple robots, it is difficult to reasonably choose the optimal walking path

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