AR Robot Trajectory Visualization for Safer Human-Robot Training
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Solution Overview
Problem
The integration of human-robot collaboration in manufacturing environments is hindered by the dangers of high-speed robot movements, lack of worker feedback in programming, and the need for improved trust and safety measures, which are not adequately addressed by existing systems.
Innovation Solution
A system and method utilizing virtual reality (VR) and augmented reality (AR) to provide immersive training for workers, allowing them to observe and interact with collaborative robots, record their movements, and adjust robot paths to accommodate individual capabilities and limitations, thereby enhancing safety and trust.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If immersive VR/AR training is implemented, then worker awareness and comfort improve, but device complexity increases
Solution Approach 1:
The patent introduces VR/AR technology as an intermediary medium between workers and collaborative robots. This virtual interface allows workers to observe robot trajectories, understand robot capabilities and limitations, and receive immersive training without direct physical interaction risks. The virtual environment serves as a safe mediator that enhances worker awareness and comfort while managing the complexity through software-based solutions.
2Object-affected harmful factors
If robot trajectories are visualized in real-time, then worker safety improves, but device complexity increases
Solution Approach 1:
The system performs preliminary visualization of robot trajectories before actual robot execution. Workers can observe the planned path and understand potential robot movements in advance through AR/VR displays. This preliminary action allows workers to mentally prepare and understand the robot's intended actions, improving safety awareness without requiring complex real-time intervention systems.
Solution Approach 2:
The patent creates virtual copies of robot trajectories and robot behavior patterns that can be observed and studied without actual robot execution. These virtual representations allow workers to understand robot capabilities, limitations, and movement patterns safely, reducing the need for complex physical safety systems while maintaining worker awareness.
3Productivity
If worker movements are recorded and used to adjust robot paths, then collaboration effectiveness improves, but loss of time increases
Solution Approach 1:
The system implements feedback mechanisms where worker movements and interactions during VR/AR training are recorded and analyzed. This feedback is used to refine and adjust robot path programming to better accommodate individual worker capabilities and limitations. The feedback loop enables continuous improvement of collaboration effectiveness while streamlining the programming process through automated data collection and analysis.
Data Source
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AI summary
A method includes determining (602) a movement of an industrial robot (305) in a manufacturing environment from a first position to a second position. The method also includes displaying (604) an image showing a trajectory of the movement of the robot on a wearable headset (315). The displaying of the image comprises at least one of: displaying an augmented reality (AR) graphical image or video of the trajectory superimposed on a real-time actual image of the robot, or displaying a virtual reality (VR) graphical image or video showing a graphical representation of the robot together with the trajectory.