Robot Path Planning with Cost Maps for Obstacle Clearance
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Solution Overview
Problem
Conventional robot path planning algorithms, such as the RRT algorithm, require extensive pre-processing to avoid obstacles, leading to time-consuming path planning and often result in paths with sharp bends or insufficient safe distance from obstacles.
Innovation Solution
A robot path planning apparatus and method that generates a cost map based on an obstacle occupancy grid, planning an initial path and calibrating it to ensure a safe distance from obstacles without pre-processing, using a controller to adjust the path based on cost values and perform primary and secondary calibrations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If pre-processing process of expanding obstacle area is performed, then collision prevention is improved, but path planning time increases
Solution Approach 1:
The patent applies preliminary action by pre-calculating and storing cost values for each grid cell based on distance to obstacles before actual path planning. This pre-processing creates a cost map that encodes safety information, allowing the path planner to quickly select safe paths without performing time-consuming obstacle expansion calculations during real-time planning.
Solution Approach 2:
The patent replaces the mechanical obstacle expansion process with a computational cost map generation system. Instead of physically expanding obstacle boundaries, the system computes distance-based cost values for each grid cell and uses these costs to guide path selection, substituting geometric manipulation with efficient numerical evaluation.
2Productivity
If conventional path planning is used, then path is found, but path includes sharp bends causing unnatural robot movement
Solution Approach 1:
The patent applies parameter changes by incorporating cost values derived from distance to obstacles into the path planning optimization process. By changing the evaluation parameter from simple path length to a cost function that includes safety distance metrics, the system generates paths that naturally avoid sharp bends and maintain safe distances, improving movement naturalness while preserving planning efficiency.
3Productivity
If conventional path planning is used, then path is found, but safe distance from obstacles is not secured
Solution Approach 1:
The patent changes the path evaluation parameter from merely minimizing path length to minimizing a cost function that incorporates distance-to-obstacle metrics. Each grid cell is assigned a cost based on its distance to the nearest obstacle, and the path planner selects paths that minimize total cost, thereby guaranteeing adequate safety margins while maintaining planning speed.
Solution Approach 2:
The patent introduces a cost map as an intermediary data structure between the obstacle map and the path planner. This cost map encodes safety information in a compact numerical form, allowing the path planner to efficiently query and evaluate path safety without direct geometric calculations, thus maintaining speed while improving reliability.
Data Source
AI summary
A robot path planning apparatus includes: a storage configured to receive an obstacle occupancy grid map, and a controller. The controller is configured to generate a cost map in which a cost corresponding to a separation distance from an obstacle to a movement area to which a robot is able to move is assigned, based on the obstacle occupancy grid map, determine a first path from a current location of the robot to a destination, and determine a second path by calibrating the first path based on the cost map.