Multi-Robot Travel Control With Zone-Based Detour Routing
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Solution Overview
Problem
Existing technologies fail to proactively prevent congestion among multiple robots by effectively balancing their paths, especially in areas where collisions are not imminent, and do not efficiently manage congestion levels in specific zones.
Innovation Solution
A server communicates with robots to determine congestion levels around designated zones, registers detour nodes for high-congestion areas, and generates detour paths that avoid overlapping with other robots' paths, ensuring balanced movement.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If multiple robots travel autonomously in a service-providing space, then task execution capability is improved, but congestion and path overlap occur reducing efficiency
Solution Approach 1:
The server continuously receives position information from multiple robots and dynamically determines congestion levels of zones. Based on this feedback, the server generates and updates detour path information in real-time, allowing robots to adjust their paths proactively before congestion occurs, thus maintaining high productivity while minimizing delays.
Solution Approach 2:
The system proactively generates detour paths before robots actually enter congested zones. By determining congestion levels in advance and providing detour path information to approaching robots, the system prevents congestion rather than reacting to it, reducing loss of time while maintaining autonomous task execution.
2Ease of operation
If congestion level of every space is determined to balance robot paths, then path balancing is improved, but computational burden increases
Solution Approach 1:
The service-providing space is divided into multiple discrete zones, and congestion levels are determined only for these specific zones rather than continuously across the entire space. This segmentation reduces computational burden while still enabling effective path balancing through detour path generation for congested zones.
Solution Approach 2:
The system focuses computational resources on determining congestion levels for specific zones where robots are likely to congregate, rather than uniformly analyzing all spaces. This localized approach maintains path balancing effectiveness while reducing overall computational complexity.
3Reliability
If detour paths are generated to avoid congested zones, then congestion prevention is improved, but path overlap with other robots may occur
Solution Approach 1:
The server receives position information from all robots and uses this feedback to generate detour paths that account for the current positions and trajectories of other robots. This ensures that detour paths are dynamically adjusted to avoid overlap with other robots while still preventing congestion in identified congested zones.
Solution Approach 2:
The system changes the parameters of detour paths based on real-time position information of robots. By adjusting detour path parameters (such as specific route coordinates and timing) according to the current state of the system, the server ensures that robots take detours that prevent both congestion and path overlap with other robots.
Data Source
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AI summary
Disclosed are a robot travel control system and robot control method. The robot travel control system according to the present disclosure comprises: a plurality of robots that travel in a predetermined space on a map; and a server that communicates with the plurality of robots and determines the level of congestion in a designated zone requiring traffic control in the predetermined space on the map. In addition, the server: registers at least one designated zone as a detour node on the basis of the determined level of congestion; detects a robot having the registered detour node in the movement path and entering within a certain range of the detour node; and generates and provides a detour path of the detected robot in consideration of the respective movement paths of the other robots present around the detour node. Accordingly, the occurrence of congestion areas can be minimized by identifying the level of congestion in a space in advance and providing detour paths so that the robots do not crowd a specific section. Consequently, it is possible for the robots to complete tasks without delay.