Mobile Redundant Robot Control for Obstacle-Aware Path Tracking
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Solution Overview
Problem
Mobile redundant robots face challenges in efficiently navigating through environments with obstacles due to their redundancy, which complicates path planning and collision avoidance.
Innovation Solution
A method for a mobile redundant robot that involves determining the position of obstacles and using the robot's base and arm to move in a way that avoids collisions, utilizing redundancy to optimize path traversal, with a controller managing the movement of the base and arm to minimize deviation from predetermined positions and paths.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If the robot uses its redundancy to avoid obstacles by moving the mobile base, then the robot's flexibility and adaptability improve, but the computational complexity of resolving redundancy and planning paths increases
Solution Approach 1:
The control task is segmented into two independent parts: (1) determining the mobile base pose that avoids obstacles while satisfying task constraints, and (2) calculating the robot arm joint angles to reach the desired position. This segmentation reduces the overall computational complexity by breaking down the redundant degree of freedom resolution into manageable sub-problems.
Solution Approach 2:
The method first determines the optimal mobile base pose before calculating the robot arm configuration. By preliminarily resolving the base position using obstacle information and task constraints, the subsequent arm angle calculation becomes simpler and more efficient, reducing overall computational burden.
2Manufacturing precision
If the robot resolves redundancy to precisely approach predetermined positions, then positioning precision improves, but the time required for computation and movement increases
Solution Approach 1:
The positioning task is divided into two sequential steps: first determining the mobile base pose that satisfies both task constraints and obstacle avoidance, then calculating the robot arm joint angles. This segmentation allows each sub-problem to be solved independently and efficiently, reducing total computation time while maintaining positioning precision.
Solution Approach 2:
The control method uses feedback from obstacle position information and task constraints to dynamically adjust the mobile base pose and robot arm configuration. By continuously monitoring and adjusting based on current state, the system achieves precise positioning without excessive computation time.
Data Source
Figure 1A~2B
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AI summary
A method for controlling a mobile robot with redundant degrees of freedom (ρ1, ρ2), wherein the robot has a mobile base (10) and a multi-axis robot arm (20), and the mobile base (10) travels along a route and at the same time the robot arm (20) travels along a predefined path (B), wherein the robot detects an obstacle (40) which is located on the route, and the route of the mobile base (10) changes in such a way that a collision with the obstacle (40) is avoided. The robot arm (20) is controlled here in such a way that the predefined path (B) is travelled along further, i.e. the TCP still remains on the predefined path (B).