Offroad Robot Path Planning Using Footprint Lookup Collision Checks
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Solution Overview
Problem
Existing path planning and collision checking algorithms for autonomous robots are computationally complex and time-consuming, especially in large and complex environments, due to the exponential growth of robot states that need to be checked.
Innovation Solution
A path planning and collision avoidance navigation system using a look-up table is implemented, where a cell grid representation of the geographic area 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 checking by querying the table for each candidate robot pose.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional path planning and collision checking algorithms are used, then collision-free paths can be generated, but the computational time and complexity increase exponentially with environment size
Solution Approach 1:
The patent pre-computes robot footprints for multiple orientations and joint states before path planning begins, storing them in a look-up table. This preliminary action eliminates the need for real-time footprint calculations during path planning, significantly reducing computational time while maintaining collision-free path generation
Solution Approach 2:
The patent creates a simplified cell grid representation (occupancy map) that copies the essential spatial information of the environment without preserving all geometric details. This abstraction allows for faster collision checking by comparing discrete grid cells instead of complex continuous geometries
2Adaptability or versatility
If the environment size and complexity increase, then more complete path planning is achieved, but the number of states to check grows exponentially
Solution Approach 1:
The patent segments the continuous configuration space into discrete cell grids and pre-computes footprints for specific orientations and joint states. This segmentation transforms the exponentially growing state space into a manageable set of discrete states that can be stored in look-up tables, allowing the system to handle larger and more complex environments without exponential computational growth
3Reliability
If real-time collision checking is performed for each candidate pose, then navigation safety is ensured, but computational speed decreases
Solution Approach 1:
The patent pre-computes and stores robot footprints for multiple orientations and joint states in a look-up table before path planning begins. During real-time operation, the system simply queries this pre-computed table rather than calculating footprints from scratch, ensuring navigation safety through accurate collision checking while maintaining high path planning speed
Solution Approach 2:
The patent replaces complex real-time geometric collision detection calculations with a simplified table-lookup mechanism. Instead of performing computationally intensive geometric intersection tests for each candidate pose, the system substitutes this with fast array access operations on pre-computed footprint data, dramatically improving speed while maintaining reliability
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.