Robotic Arm Path Planning With Dynamic Resolution Obstacle Avoidance
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Solution Overview
Problem
Existing robotic path planning methods either lack efficiency, as deterministic methods are slow and non-deterministic methods do not guarantee a feasible path, and fail to provide a path that is both fast and optimal.
Innovation Solution
A system and method for robot path planning that includes an obstacle detector, position-dependent dynamic resolution generation, neighbor reduction, path optimization, and path smoothing units, which dynamically adjust the discretization resolution based on distance to the goal, reduce the search space by prioritizing relevant neighbors, and use a cost function to minimize the path length while avoiding obstacles, ultimately employing the A* algorithm for optimization.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If deterministic methods (e.g., A* algorithm) are used to explore all possible moves in the grid by minimizing a cost function, then the generated path is unique and optimal, but the planning process becomes slow
Solution Approach 1:
The patent segments the high-dimensional joint angle space into a hierarchical grid structure with different resolutions. Coarse grids are used for long-range planning while fine grids are used for local precision, allowing the algorithm to explore fewer states while maintaining path optimality.
Solution Approach 2:
The patent applies different grid resolutions to different regions of the configuration space. Areas closer to the goal or containing obstacles use finer resolution for accurate path planning, while distant regions use coarser resolution to reduce computational burden.
2Productivity
If non-deterministic methods (e.g., RRT algorithm) are used to explore the next movement randomly with a bias toward large unsearched areas, then the planning process is fast, but the method does not guarantee a feasible path and the path length is unbounded
Solution Approach 1:
The patent performs preliminary path planning using a coarse grid to establish a rough trajectory before refining it with finer grids. This preliminary action guides the random exploration of RRT toward promising regions, ensuring feasibility while maintaining speed.
Solution Approach 2:
The patent dynamically adjusts the grid resolution and exploration strategy based on the robot's current position and distance to the goal. As the robot approaches the goal, the resolution increases to ensure precise and feasible path completion.
3Ease of operation
If the continuous space of joint angles is discretized as a high-dimensional grid to perform path planning, then the path can be planned systematically, but the number of possible moves increases exponentially with the number of joints
Solution Approach 1:
The patent segments the high-dimensional search space into multiple lower-dimensional layers with different resolutions. Each layer handles a specific range of distances from the goal, reducing the effective dimensionality and number of states that need to be explored at any given time.
Solution Approach 2:
The patent introduces a new dimension representing the distance to the goal, organizing the search space hierarchically. This transforms the problem from exploring a single high-dimensional grid to navigating through multiple lower-dimensional grids in sequence, significantly reducing computational complexity.
Data Source
AI summary
The present teaching relates to a method and system for path planning. Information of a current pose of a robotic arm having a plurality of operable segments is obtained. The information includes a plurality of values, each of which corresponds to an angle formed between consecutive operable segments of the robotic arm. A desired pose where the robotic arm needs to reach is also obtained. An angle step-value is computed for the current pose of the robotic arm based on a function of a distance between the current pose and the desired pose, wherein the angle step value is to be used to determine a plurality of candidate next poses of the plurality of operable segments. One or more of candidate next poses is selected based on at least one criterion, and a trajectory is determined from the current pose to the desired pose based on the selected next poses.