Robot Return-to-Home Path Planning in 3D Workcells
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Solution Overview
Problem
Industrial robots often get 'stuck' in complex workspaces with multiple obstacles and moving parts, requiring manual operator intervention or pre-defined recovery paths that are difficult to create, especially in tight quarters, to safely return to their home position without collisions.
Innovation Solution
A technique that uses a virtual 3D simulation environment to emulate the physical robot and workcell in real time, calculating a collision-free return-to-home path using a specialized Rapidly-Exploring Random Tree (RRT) algorithm and move feasibility checks, which considers robot joint positions and prohibited zones, and transfers the computed path back to the physical robot for execution.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual jogging is used to return robot to home position, then operator can control robot movement, but operator skill requirement increases and collision risk increases in tight quarters
Solution Approach 1:
The system performs automatic path planning and execution without requiring operator intervention. The robot autonomously calculates its own recovery path and executes it, eliminating the need for operator skill and reducing collision risk through algorithmic precision rather than human judgment.
Solution Approach 2:
The manual mechanical control via teach pendant is replaced with an automated computational system. The path planning algorithm substitutes for operator manipulation, using virtual environment simulation and automated path calculation to determine safe recovery movements without human intervention.
2Extent of automation
If pre-defined recovery path programs are used, then robot can return home automatically, but creating comprehensive paths for all situations is difficult in complex environments
Solution Approach 1:
The system transitions from static pre-defined paths to dynamic on-demand path generation. When the robot needs recovery, the system calculates a new path based on current robot position, orientation, and environmental conditions, allowing adaptation to any situation without requiring pre-programming of all possible scenarios.
Solution Approach 2:
The system performs preliminary virtual simulation and path validation before executing the recovery path. By pre-calculating and verifying the path in the virtual environment, the system ensures safety and feasibility before actual execution, eliminating the need for comprehensive pre-defined paths for every possible situation.
3Measurement precision
If virtual 3D simulation environment is used for real-time emulation, then accurate path calculation is achieved, but computational complexity increases
Solution Approach 1:
The system creates a virtual copy of the physical workcell environment including robot geometry, obstacles, and constraints. This digital twin allows accurate path calculation through simulation without requiring complex physical testing, and the virtual model can be updated to reflect changes in the physical environment.
Solution Approach 2:
The system performs preliminary path calculation and validation in the virtual environment before executing in the physical system. This pre-simulation approach allows complex computational work to be done beforehand, ensuring accuracy while keeping the actual execution simple and fast.
Data Source
AI summary
A technique for automatically finding a collision-free return-to-home path for a robot. The technique includes running a simulated virtual 3D environment which emulates the physical robot and workcell in real time, including the positions and poses of all robots, workpieces and obstacles in the workcell. Upon request by an operator, a return-to-home path search is executed based on the virtual 3D environment, where the path search calculates a solution which moves the robot from a current position to its home or recovery position while avoiding collisions with other robots, workpieces or objects in the workcell. In addition to collision avoidance, the path search considers other constraints such as prohibited zones in the workspace and robot joint positions. When the recovery path is computed, the solution program is sent back to the physical environment for execution by the physical robot.