Coordinated Vehicle Path Planning via Local Graph Sharing
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Solution Overview
Problem
Coordinated planning between autonomous and semi-autonomous vehicles is hindered by unknown obstacles in their environment, compromising mission plans and success.
Innovation Solution
A method and system for path planning that involves determining local graphs from individual vehicles, assembling a global graph through communication networks, and re-planning as necessary to ensure connectivity and objective achievement, using sensor information and nodes/edges to navigate and avoid obstacles.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If vehicles operate independently without sharing graph information, then each vehicle can maintain simple local planning, but the overall mission coordination and obstacle avoidance capability deteriorates
Solution Approach 1:
The system divides the global graph into multiple local graphs, each maintained by individual vehicles. Each vehicle independently manages its own local graph containing only the portion of environment relevant to its current objectives, rather than all vehicles sharing a single comprehensive global graph. This segmentation reduces the information burden on each vehicle while maintaining coordinated mission capability through selective information sharing.
Solution Approach 2:
Each vehicle maintains a local graph with quality and detail appropriate to its specific needs and local environment, rather than all vehicles maintaining identical comprehensive graphs. The local graphs contain selectively relevant information about obstacles, pathways, and objectives specific to each vehicle's current mission context, improving efficiency while maintaining overall mission coordination.
2Reliability
If vehicles share complete global graph information, then coordinated planning and obstacle avoidance improve, but communication bandwidth and processing requirements increase
Solution Approach 1:
The system extracts and shares only the essential portions of graph information needed for coordinated planning, rather than transmitting complete global graphs between all vehicles. Each vehicle shares selective information about relevant obstacles, pathways, and mission objectives with others, reducing communication bandwidth requirements while maintaining coordinated planning capability.
Solution Approach 2:
Vehicles perform preliminary processing of graph information locally before sharing, pre-filtering and pre-organizing data to identify only the most relevant information for sharing with other vehicles. This preliminary action reduces the quantity of information that needs to be transmitted over communication networks while ensuring that essential coordinated planning data is available.
3Measurement precision
If vehicles maintain detailed local graphs of their environment, then local navigation accuracy improves, but the ability to coordinate with other vehicles and achieve global mission objectives deteriorates
Solution Approach 1:
The system merges multiple local graphs into a coordinated global mission picture through selective information sharing and integration. Each vehicle maintains detailed local graph information for accurate local navigation, while simultaneously integrating relevant portions of other vehicles' local graphs to achieve global mission coordination and adaptability.
Data Source
AI summary
A method for path planning for a plurality of vehicles in a mission space includes determining, with a processor, information indicative of a first local graph of a first vehicle; receiving, with the processor over a communication link, information indicative of a second local graph from a second vehicle; assembling, with the processor, information indicative of a global graph in response to the receiving of the second local graph; wherein the global graph includes information assembled from the first local graph and the second local graph; and wherein the global graph indicates connectivity of objectives for each vehicle of the plurality of vehicles in the mission space.