Multi-Robot Route Planning With Area Capacity Constraints
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Solution Overview
Problem
Conventional multiple moving body route planning algorithms fail to effectively detect conflicts across multiple graph elements in complex environments, leading to inefficiencies and potential collisions or deadlocks among autonomous moving bodies.
Innovation Solution
An information processing apparatus and method that groups graph elements into areas with defined capacities, allowing for conflict detection and route planning that respects these capacities, using a UI for area setting and applying algorithms like CBS to ensure no conflicts exceed the set limits.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional conflict detection is performed for each graph element, then the detection process is simple and computationally efficient, but conflicts across multiple graph elements cannot be detected
Solution Approach 1:
The environment is divided into multiple areas, each comprising a set of graph elements (nodes and edges). This segmentation allows conflict detection to be performed at the area level rather than individual graph element level, enabling detection of conflicts that span multiple graph elements while maintaining computational manageability through hierarchical organization.
Solution Approach 2:
The patent introduces a new dimension of organization by grouping graph elements into areas with defined capacities. This transforms the conflict detection problem from a single-level graph element check to a multi-level system where areas aggregate graph elements and enforce capacity constraints, enabling detection of跨区域 conflicts without examining every individual graph element pair.
2Reliability
If area-based capacity constraints are implemented, then conflicts across multiple graph elements can be detected, but the system complexity and computational load increase
Solution Approach 1:
Areas and their capacity constraints are pre-defined before route planning begins. This preliminary organization of the environment into capacity-constrained areas allows the route planning algorithm to operate with simplified conflict detection logic, checking whether proposed routes violate area capacities rather than performing complex real-time analysis of all graph element interactions.
Solution Approach 2:
Areas serve as intermediary structures between individual graph elements and the route planning algorithm. The areas aggregate multiple graph elements and enforce capacity constraints, acting as a mediator that simplifies the route planning process by providing a higher-level abstraction for conflict detection without losing the detailed graph structure information.
Data Source
AI summary
Provided is an information processing apparatus includes a graph structure generation unit and a route planning unit. The graph structure generation unit sets an area including a plurality of graph elements in a graph including a node and an edge as a graph element. The route planning unit plans a route of a plurality of moving bodies (MB) in a graph such that a conflict of moving bodies (MB) exceeding the capacity of the area does not occur in the area.