Time-Space Path Planning for Multi-Obstacle Surface Navigation
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Solution Overview
Problem
Existing automatic navigation systems for unmanned vehicles face difficulties in planning paths in complex and dynamic environments due to the lack of consideration for multiple obstacles and constraints, such as COLREGs and manipulation performance.
Innovation Solution
A method and system for open-surface navigation using a time-space map, which divides the environment into time-space grids with temporal and geographic information, determines obstacle status and volumes, and calculates navigable and unnavigable grids to find an optimal path for the vehicle.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If traditional single-obstacle avoidance algorithms (velocity obstacle, artificial potential field) are used, then the system is simple to implement, but it cannot handle complex dynamic environments with multiple obstacles and constraints
Solution Approach 1:
The patent segments the navigation problem into multiple independent modules: time-space map construction, obstacle status determination, navigable grid identification, and path planning. Each module handles a specific aspect of the complex environment, allowing the system to manage multiple obstacles and constraints through systematic decomposition rather than monolithic processing.
Solution Approach 2:
The patent introduces a time dimension to the traditional 2D space map, creating a 4D time-space map that incorporates temporal information. This dimensional expansion allows the system to predict future obstacle positions and plan paths that account for dynamic movements, enabling handling of multiple moving obstacles and time-varying constraints that were impossible in conventional 2D approaches.
2Productivity
If real-time path planning is implemented in complex dynamic environments, then navigation responsiveness is improved, but computational time and processing load increase
Solution Approach 1:
The patent performs preliminary actions by pre-processing environmental data to construct the time-space map and pre-calculating obstacle trajectories and volumes before actual path planning occurs. By preparing the navigable and unnavigable grid classifications in advance, the system reduces computational burden during real-time path planning, enabling responsive navigation without excessive processing delays.
Solution Approach 2:
The patent implements dynamic adaptability by adjusting the resolution and coverage of the time-space map based on current navigation needs and environmental complexity. The system dynamically updates obstacle status and navigable grids as new information becomes available, allowing efficient real-time planning that adapts to changing conditions without requiring complete recomputation of the entire navigation space.
3Measurement precision
If the time-space map includes detailed temporal and geographic information for accurate path planning, then path accuracy is improved, but data processing complexity increases
Solution Approach 1:
The patent segments the time-space map into discrete grid cells, each storing simplified temporal and geographic information. This segmentation allows the system to maintain detailed spatial and temporal data for accurate path planning while reducing processing complexity by operating on discrete units rather than continuous data, enabling efficient queries and comparisons across the navigation space.
Data Source
AI summary
The present disclosure is related to systems and methods for open-surface navigation for a vehicle based on a time-space map. The method includes determining a time-space map of a first area. The time-space map may include a plurality of time-space grids. Each time-space grid may include temporal information and geographic information corresponding to the time-space grid. The method also includes obtaining obstacle status of each of one or more obstacles corresponding to a first time period. The method also includes determining a plurality of navigable grids and a plurality of unnavigable grids among the plurality of time-space grids, based on the obstacle status. The method further includes determining a path for the vehicle based on the plurality of navigable grids.