Offroad Robot Path Planning With Lookup-Table Collision Checking
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Solution Overview
Problem
Path planning and collision checking for autonomous robots in complex environments are computationally intensive due to the large number of robot states that need to be checked, leading to increased computational effort and time in generating collision-free paths.
Innovation Solution
A path planning and collision avoidance navigation system using a look-up table, where a cell grid representation of the environment is generated, and pre-computed footprints of the robot at various orientations and joint states are stored in a look-up table, allowing for fast collision checks by querying the table for candidate paths.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional path planning and collision checking algorithms are used to generate collision-free paths, then path planning accuracy is improved, but computational time and complexity increase exponentially
Solution Approach 1:
The patent pre-computes robot footprints for multiple orientations and joint states before path planning begins. These pre-computed footprints are stored in a lookup table, allowing the system to quickly retrieve and use them during collision checking without performing real-time computations. This preliminary preparation significantly reduces the computational time required during actual path planning while maintaining accurate collision detection.
Solution Approach 2:
The patent creates simplified representations of the robot's footprint at different orientations and joint states, storing these copies in a lookup table. Instead of computing complex robot geometries during path planning, the system uses these pre-created copies for rapid collision checking. This copying approach maintains the essential collision detection capability while dramatically reducing computational complexity.
2Area of stationary object
If the size and complexity of the environment increases, then path planning coverage is improved, but the number of states to check grows exponentially
Solution Approach 1:
The patent segments the continuous space of robot orientations and joint states into discrete categories. By dividing the orientation space into discrete angles and joint states into specific configurations, the system creates a manageable grid structure for the lookup table. This segmentation allows the system to handle larger environments by organizing states in a structured manner, reducing the exponential growth of complexity while maintaining comprehensive coverage.
Data Source
AI summary
A robot generates a cell grid (e.g., occupancy grid) representation of a geographic area. The occupancy grid may include a plurality of evenly sized cells, and each cell may be assigned an occupancy status, which can be used to indicate the location of obstacles present in the geographic area. Footprints for the robot corresponding to a plurality of robot orientations and joint states may be generated and stored in a look-up table. The robot may generate a planned path for the robot to navigate within the geographic area by generating a plurality of candidate paths, each candidate path comprising a plurality of candidate robot poses. For each candidate robot pose, the robot may query the look-up table for a corresponding robot footprint to determine if a collision will occur.