Dynamic Path Generation Using Cost History Queue
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Solution Overview
Problem
Existing path generation methods for mobile automation systems in complex environments are computationally demanding and time-consuming, leading to interruptions when obstacles are detected, as they often require discarding previously generated paths and initiating a new search of the environmental map.
Innovation Solution
A method for dynamic path generation that involves generating multiple paths, selecting an optimal path based on cost, storing costs in a history queue, and re-planning within an initial search space defined by retrieved costs when obstacles are detected, allowing for efficient re-routing without discarding the entire search tree.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a new search of the environmental map is initiated when an obstacle is detected, then a new path can be found to avoid the obstacle, but the operation of the apparatus is interrupted and time is lost
Solution Approach 1:
The system performs preliminary actions by pre-generating multiple candidate paths and storing them in a data structure before obstacles are detected. When an obstacle is encountered, the apparatus can immediately select from pre-computed alternative paths without initiating a new search, thereby eliminating re-planning time while maintaining reliable path finding
Solution Approach 2:
The patent implements a dynamic path management system where multiple paths are generated and stored with associated cost values. The system dynamically selects the optimal path based on real-time obstacle detection, switching between pre-generated paths without interruption. This dynamic approach allows the apparatus to adapt to changing environmental conditions while maintaining continuous operation
2Loss of time
If multiple paths are generated and stored for re-planning purposes, then re-planning time is reduced when obstacles are detected, but the computational demand and memory usage increase
Solution Approach 1:
The system manages computational complexity by parameterizing path generation with cost values and organizing paths in a data structure sorted by cost. This parameter-based organization allows efficient retrieval of optimal paths without requiring complex real-time computations. The cost parameter serves as a key for both path generation and selection, simplifying the overall system complexity while enabling rapid re-planning
Solution Approach 2:
The patent segments the path generation process into distinct phases: generating multiple candidate paths, assigning cost values to each path, storing them in an organized data structure, and selecting the optimal path based on cost. This segmentation allows each phase to be optimized independently, reducing overall computational demand while maintaining the ability to provide multiple path options for rapid re-planning
Data Source
AI summary
A method of dynamic path generation in a navigational controller includes: generating (i) a plurality of paths extending from a starting location to a goal location, and (ii) a cost for each of the paths; selecting, based on the costs, an optimal path for execution from the plurality of paths; storing a subset of the costs in a cost history queue; responsive to detecting an obstacle during execution of the optimal path, retrieving one of the costs from the cost history queue; determining an initial re-planning search space based on the cost retrieved from the cost history queue; and initiating generation of a re-planned path within the initial re-planning search space.