Robot Recovery Path Control After Obstruction Entanglement
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Solution Overview
Problem
Robots often struggle to recover from obstructed states, such as collisions with obstacles, requiring manual intervention by skilled users, leading to prolonged recovery times and reduced productivity.
Innovation Solution
A robot control device and method that acquires environment and robot specification information after an obstruction occurs, generating a path for the robot to safely recover to a safe pose using 3D-measurement data and CAD data, allowing for automatic and efficient recovery.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Extent of automation
If reverse sequence execution of path is used for recovery, then the robot can recover to home position automatically, but the robot cannot recover when entangled with obstacle in complex manner
Solution Approach 1:
The system performs preliminary actions by acquiring environment information at the periphery of the robot before generating the recovery path. This includes obtaining 3D-measurement data and identifying shapes and positions of objects in advance, allowing the robot to plan a safe recovery path that avoids obstacles before the recovery motion begins, thereby ensuring reliability in complex entangled states.
Solution Approach 2:
The invention replaces the mechanical reverse sequence execution method with an information-based control system. Instead of simply reversing motion commands, the system uses 3D-measurement data, object shape identification, and path generation algorithms to compute a new safe recovery path, substituting mechanical trial-and-error with intelligent planning based on environmental perception.
2Reliability
If manual operation by skilled user is used for recovery, then the robot can recover to safe pose, but the time to recover is prolonged
Solution Approach 1:
The robot performs self-service recovery by autonomously acquiring environment information, identifying obstacles, generating a recovery path, and executing the recovery motion without human intervention. The system uses its own sensors to perceive the environment, processes the data to identify object shapes and positions, and automatically computes and follows a safe recovery path, eliminating the need for skilled manual operation while maintaining recovery safety.
Solution Approach 2:
The system implements feedback by continuously acquiring environment information at the periphery of the robot during the recovery process. The path generation section uses this real-time feedback data to adjust and optimize the recovery path, ensuring the robot can safely navigate around obstacles that may be in complex positions, thereby achieving both speed and safety in recovery.
3Productivity
If reverse path retracing is used for recovery, then the robot can return to home position, but the robot may collide again or trip limit switch
Solution Approach 1:
The system performs preliminary action by acquiring environment information and identifying obstacle shapes and positions before generating the recovery path. This advance preparation allows the path generation section to compute a trajectory that proactively avoids obstacles and limit switches, preventing collisions before they occur rather than reacting to them during recovery.
Solution Approach 2:
The invention replaces the simple mechanical reverse path retracing with an intelligent path generation system that uses 3D-measurement data and object shape identification. This substitution transforms the recovery process from blind reverse motion to informed navigation, where the robot computes a safe path that avoids harmful factors like collisions and limit switch tripping while maintaining fast recovery speed.
Data Source
AI summary
When occurrence of an obstruction has been detected during action of a robot, a path generation section acquires environment information at a periphery of the robot after obstruction occurred, robot specification information, and safe pose information representing a recovery-pose for the robot, and generates a path of the robot from a pose after obstruction occurred to a safe pose based on the acquired information.