MR Robot Training Interaction for Realistic Disaster Response
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Solution Overview
Problem
Current training systems for disaster response robots are limited as they primarily focus on virtual environments, failing to provide a realistic experience for trainees operating actual robots in disaster scenarios, as the robots do not effectively recognize and respond to virtual disaster tasks, leading to a disconnect between virtual and actual environments.
Innovation Solution
An interaction training system utilizing a Mixed Reality (MR) environment that includes a scenario module, MR environment implementing module, interaction module, robot driving module, and control module to create a realistic disaster scenario where trainees can operate robots, with the interaction module determining whether events are actual or virtual and restricting robot commands to simulate real-world responses.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If a virtual environment is used for training, then the training can be conducted without physical disaster scenarios, but the trainee cannot feel the same as the actual environment
Solution Approach 1:
The patent introduces an MR environment as an intermediary that overlays virtual disaster elements (fire, obstacles, victims) onto the actual training space. This mediator allows the trainee to experience both the convenience of virtual training and the realism of actual environment perception, resolving the contradiction between ease of setup and training realism.
Solution Approach 2:
The system merges the virtual training environment with the actual physical environment by combining MR technology with real-world disaster response training. This integration allows virtual disaster elements to coexist with physical robots and training spaces, providing both convenience and realism simultaneously.
2Adaptability or versatility
If the robot operates in a virtual environment, then the training scenario can be flexibly changed, but the robot cannot recognize virtual training events
Solution Approach 1:
The interaction module provides feedback to the robot about virtual training events detected in the MR environment. When the robot approaches or interacts with virtual elements (fire, obstacles, victims), the system provides positional and contextual feedback, enabling the robot to recognize and respond to virtual events while maintaining scenario flexibility.
Solution Approach 2:
The MR environment acts as an intermediary that translates virtual disaster elements into robot-recognizable information. The interaction module mediates between the virtual MR elements and the physical robot, providing the robot with awareness of virtual events through coordinate transformations and event detection.
3Ease of operation
If the trainee operates the robot without restrictions, then the operation is smooth, but the trainee cannot recognize virtual training events
Solution Approach 1:
The interaction module preemptively restricts robot driving when virtual training events are detected, preventing the trainee from accidentally ignoring or passing through critical virtual elements. This preliminary restriction ensures the trainee notices and responds to virtual events like fire and obstacles before the robot can harmlessly pass them by.
Solution Approach 2:
The interaction module serves as an intermediary between the trainee's control inputs and the robot's actual movement. It monitors the MR environment and selectively restricts robot motion when virtual training events are present, mediating between smooth operation and event recognition requirements.
Data Source
AI summary
The present invention relates to an interaction training system of a robot with a Mixed Reality (MR) environment, and to a training system in which a robot including a camera and a sensor is driven in a training space and a virtual environment like an actual environment is provided to a trainee to train the trainee.