Path Planner Sufficiency Verification via Logical Satisfiability
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Solution Overview
Problem
Existing path planning systems for vehicles, particularly in the aerospace domain, face challenges in verifying the sufficiency of path planners to avoid obstacles, especially in complex scenarios with exponentially large choice spaces.
Innovation Solution
A method and system that iteratively analyze the sufficiency of a path planner by representing paths as disjunctions of logical terms, conjoining them with previous paths, determining satisfiability conditions, and adding obstacles to the path planner until stopping conditions are met, thereby providing an indication of the path planner's sufficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If formal verification using automatic theorem provers is used for ACAS-X planner, then verification completeness is improved, but device complexity and computational scalability deteriorate
Solution Approach 1:
The verification process is segmented into iterative batches where obstacles are added in groups rather than all at once. Each iteration verifies a subset of obstacle configurations, dividing the exponentially large verification space into manageable segments that can be processed sequentially with controlled computational complexity.
Solution Approach 2:
The system performs preliminary actions by pre-adding obstacles that are likely to create challenging verification cases early in the iteration process. This preliminary action guides the path planner to develop more robust paths that will withstand subsequent additions of obstacles, improving verification efficiency.
2Reliability
If exhaustive verification of all obstacle configurations is performed, then verification completeness is improved, but loss of time increases
Solution Approach 1:
The verification process uses periodic action by iterating through obstacle additions in structured cycles. Each iteration adds obstacles periodically and checks for path validity, allowing the system to verify completeness progressively rather than waiting for exhaustive enumeration of all possible configurations.
Solution Approach 2:
The system implements feedback mechanisms where verification results from each iteration inform subsequent obstacle additions. When the path planner successfully navigates added obstacles, this feedback confirms sufficiency for those configurations, allowing the system to avoid redundant verification of equivalent scenarios and reduce total computational time.
Data Source
AI summary
Techniques for establishing the sufficiency of a path planner to avoid multiple obstacles in planning a path from a starting location to a destination location is presented. The techniques can include: iterating, until a stopping condition occurs: obtaining, from the path planner, a path from the starting location to the destination location; representing the path from the starting location to the destination location as a disjunction of logical terms; conjoining the disjunction of terms to a conjunction of terms representing previously considered paths; determining a satisfiability condition of the conjunction of terms; and for a positive satisfiability condition, adding at least one corresponding obstacle of the plurality of obstacles to the path planner; and providing an indication of sufficiency of the path planner to avoid the obstacles in planning a path from the starting location to the destination location based on the stopping condition.