Robot Motion Learning with Trajectory Compatibility Checking
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Solution Overview
Problem
Existing motion capture robotic programming systems are not fully satisfactory for allowing users without industrial robotics knowledge to easily and accurately program robotic devices, as they do not ensure compatibility of trajectories with the robotic device's degrees of freedom and workspace parameters.
Innovation Solution
A motion learning system that includes a workspace storage module, pointer modules for user-driven trajectory capture, a post-processing module to ensure trajectory compatibility, and a program generation module to create compatible robotic language, along with visualization and simulation tools to validate and modify trajectories, and an alert system for incompatible paths.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If a motion capture robotic programming system is used to allow users without industrial robotics knowledge to program robotic devices, then the ease of operation is improved, but the reliability of trajectory compatibility with robotic device capabilities deteriorates
Solution Approach 1:
The patent introduces a learning device as an intermediary between the user and the robotic system. This learning device captures user movements and translates them into robotic programming commands, mediating the interaction to ensure both ease of use and trajectory compatibility. The learning device acts as a bridge that converts natural human motion into precise robotic control signals that respect the robot's kinematic constraints.
Solution Approach 2:
The system implements feedback mechanisms where the robotic system's response to captured trajectories is analyzed and used to refine the programming process. The system provides feedback on trajectory compatibility, allowing users to adjust their movements to achieve desired outcomes while maintaining compatibility with the robotic device's capabilities.
2Manufacturing precision
If traditional robotic programming methods are used to ensure accurate trajectory execution, then the manufacturing precision is improved, but the device complexity increases
Solution Approach 1:
The patent employs copying by capturing the user's actual movement trajectory and using this captured motion as the basis for robotic execution. Instead of requiring users to program complex trajectories theoretically, the system copies the user's natural motion and adapts it for robotic execution, maintaining accuracy while reducing programming complexity.
Solution Approach 2:
The system replaces traditional mechanical programming approaches with a motion capture-based approach. Instead of manually configuring robotic joints and calculating trajectories through complex mechanical computations, the system uses sensors and algorithms to capture and translate human motion, substituting mechanical programming complexity with automated motion processing.
3Productivity
If motion capture systems are used to simplify robotic programming, then the productivity is improved, but the measurement precision of trajectory compatibility deteriorates
Solution Approach 1:
The system performs preliminary actions by capturing and processing user movements before actual robotic execution. The learning device records trajectories in advance, allowing the system to analyze and validate compatibility with robotic capabilities before committing to execution, thus maintaining precision while enabling rapid programming.
Solution Approach 2:
The patent applies dynamics by making the programming system adaptive and flexible. The motion capture system dynamically adjusts to user movements in real-time, and the robotic system dynamically adapts the captured trajectories to fit its kinematic constraints, maintaining measurement precision while improving programming speed through flexible, real-time processing.
Data Source
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AI summary
- System and method for motion learning to program at least one robotic device. - The system includes a workspace (3) memory module (5), at least one pointer (6) associated respectively with an effector (4) of a robotic device (2), a trajectory capture module (8) for the movement carried out by the pointer(s) (6), a post-processing module (10) to determine a compatible trajectory for the effector(s) (4) and a save module (11), configured to save the compatible trajectory for each of the robotic devices (2).