Occupancy Grid Free Space Detection in Cluttered Robot Environments
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Solution Overview
Problem
Existing robotic path planning systems face challenges in accurately identifying free space in cluttered environments, as they often produce incorrect data by marking only grid vertices as occupied and ignoring partially occupied grids, leading to inefficient movement planning.
Innovation Solution
A processor-implemented method and system for free space detection that generates an occupancy grid map, seeds unified segments by merging free grids, and executes convex expansions to identify and mark free space, allowing for more accurate robotic path planning in cluttered environments.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If existing systems mark only grid vertices as occupied in occupancy grid maps, then the path planning computation is simplified, but the free space identification accuracy deteriorates
Solution Approach 1:
The patent segments the occupancy grid map into unified free space segments by merging adjacent free grids, rather than treating each grid independently. This segmentation approach maintains computational tractability while improving accuracy by considering spatial continuity of free spaces.
Solution Approach 2:
The patent merges adjacent free grids into unified segments to accurately represent continuous free spaces. By combining multiple free grids that form a connected region, the system captures the true extent of navigable areas without excessive computational overhead.
2Reliability
If existing systems mark partially occupied grids as occupied, then obstacle avoidance is ensured, but available free space for robotic movement is reduced
Solution Approach 1:
The patent applies different marking strategies to different regions of the grid map based on local occupancy characteristics. Fully occupied grids are marked as obstacles, while partially occupied grids are marked as free space, allowing robots to utilize available navigation areas while maintaining safety margins.
Solution Approach 2:
Instead of marking all potentially occupied grids as occupied (excessive action), the system selectively marks only fully occupied grids, leaving partially occupied grids as free space (partial action). This approach maximizes usable free space while maintaining adequate obstacle avoidance through proper bounding box construction.
3Speed
If existing systems use vertex-based occupancy marking, then the data processing is faster, but incorrect free space data is produced
Solution Approach 1:
The patent performs preliminary construction of accurate bounding boxes around obstacles before path planning begins. By pre-processing the occupancy grid to correctly identify and mark all grids occupied by obstacles (including those not containing vertices), the system eliminates the need for complex runtime corrections while maintaining processing efficiency.
Data Source
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AI summary
Robots are used extensively in different applications so as to perform specific tasks. However, the robots are required to move around in a location where they are present, so as to perform the tasks. For path planning, free space identification is performed by the robots during which obstacles are detected and free space is identified. However, the existing systems for path planning struggle to identify free space in cluttered environments. The disclosure herein generally relates to robotic path planning, and, more particularly, to a method and system for free space detection in a cluttered environment for robotic path planning. The system inscribes obstacles in bounding boxes and all unit grids inscribed by the bounding boxes are considered as occupied. Further, by seeding the occupancy grid map, the system identifies unified segments and corresponding seeds. Further a convex expansion is executed in the occupancy grid map to detect the free space.