VR Teleoperation for Adaptive Multi-Robot AI Training
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Solution Overview
Problem
Current robotic systems and AI technologies face challenges in fulfilling complex and variable manufacturing jobs due to their inability to adapt to diverse contexts, leading to a skills gap and unemployment issues among low-skill workers.
Innovation Solution
A scalable teleoperation system utilizing virtual reality (VR) to allow low-skill workers to remotely control robots through a multi-user, multi-robot framework, where users can monitor and control robots in a virtual environment, with AI-assisted automation for efficient task completion.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Extent of automation
If robotic systems use AI to fulfill complex manufacturing jobs, then automation extent improves, but adaptability to diverse contexts deteriorates
Solution Approach 1:
The patent introduces teleoperators as an intermediary between human operators and robotic systems. These teleoperators wear VR headsets and use haptic feedback devices to remotely control robots in complex manufacturing environments, enabling adaptive decision-making while maintaining high automation levels through the intermediary human-in-the-loop control mechanism
Solution Approach 2:
The system dynamically adjusts the level of human involvement based on task complexity and context variability. For routine tasks, the system operates autonomously with high automation, while for complex variable tasks, it dynamically transitions to teleoperated mode, creating a flexible hybrid automation system that adapts to diverse manufacturing contexts
2Adaptability or versatility
If teleoperation system allows multiple users to control multiple robots, then adaptability improves, but device complexity deteriorates
Solution Approach 1:
The patent implements a universal virtual reality control environment that serves multiple functions: displaying robot states, enabling user selection, providing haptic feedback, and managing teleoperation connections. This single universal VR interface handles all multi-user multi-robot interactions, reducing the need for separate control systems for each robot-user pair and simplifying the overall system architecture
3Reliability
If users spend more time monitoring and controlling robots, then task success rate improves, but loss of time deteriorates
Solution Approach 1:
The system implements autonomous monitoring where robots and the system automatically track task progress, detect anomalies, and manage operational states without requiring continuous user attention. The VR interface only requires user intervention when actual teleoperation is needed, allowing users to maintain high task success rates while minimizing time spent monitoring, as the system serves itself through automated surveillance and exception-based alerting
Data Source
AI summary
In some aspects, a system comprises a computer hardware processor and a non-transitory computer-readable storage medium storing processor-executable instructions for receiving, from one or more sensors, sensor data relating to a robot; generating, using a statistical model, based on the sensor data, first control information for the robot to accomplish a task; transmitting, to the robot, the first control information for execution of the task; and receiving, from the robot, a result of execution of the task.