Remote-Controlled Robot Collision Prevention via Video Color-Mapping
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Solution Overview
Problem
Conventional systems for remote-controlled mobile robots struggle to effectively prevent collisions with obstacles, particularly when using small screens for control, as they require expensive distance measuring sensors and may not clearly display obstacle information, making it difficult for remote users to recognize obstacles in time.
Innovation Solution
A system that color-maps potential collision areas on the control appliance screen, generates an alarm signal before a collision, and displays motion and speed information as icons, allowing users to recognize obstacles and prevent collisions effectively.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Weight of moving object
If a small screen is used for the control appliance, then the device becomes more portable and easier to carry, but it becomes difficult to display obstacle information clearly and hard for the user to recognize obstacles in time
Solution Approach 1:
The patent applies color-mapping technology to overlay obstacles with distinct colors on the screen. Different colors represent different types of obstacles or different distance levels, enabling users to quickly recognize obstacles even on small screens. This color-based visual encoding transforms complex obstacle information into intuitive color-coded displays that are easily distinguishable at small sizes.
Solution Approach 2:
The patent superimposes obstacle information as a semi-transparent layer over the video feed from the robot's camera. This creates a multi-dimensional display where spatial information from the camera view is combined with processed obstacle detection data, allowing users to perceive obstacle locations and types without losing the contextual video background, thereby maximizing information density on small screens.
2Measurement precision
If expensive distance measuring sensors are used, then collision detection accuracy is improved, but the system cost increases significantly
Solution Approach 1:
The patent creates a virtual copy of the physical environment by processing video images from the robot's camera to generate an overhead map and detect obstacles. Instead of using expensive physical distance measuring sensors, the system uses image processing algorithms to create a digital representation of obstacle locations and distances, achieving accurate collision detection through software-based virtual modeling rather than costly hardware sensors.
Solution Approach 2:
The patent replaces mechanical distance measuring sensors with an optical-based image processing system. By using the robot's existing camera and applying computer vision algorithms to analyze video frames, the system substitutes expensive mechanical sensing hardware with a software-based optical processing approach, maintaining measurement precision while significantly reducing system cost.
3Measurement precision
If the field of view (FOV) of the CCD is small, then the distance measurement precision is improved, but it becomes difficult to distinguish the shape of the obstacle and inform the remote user of obstacle information
Solution Approach 1:
The patent merges multiple data sources and processing results into a unified display. It combines the video feed from the camera, the processed overhead map showing obstacle locations, and color-coded obstacle type information into a single integrated view. This merging allows the system to use a narrow FOV CCD for precise distance measurement while still providing comprehensive obstacle information through the synthesized overhead map and color coding that overlays additional contextual data.
Solution Approach 2:
The patent transforms the limited two-dimensional camera view into a three-dimensional understanding of the environment by generating an overhead map that shows obstacle locations, distances, and types. This dimensional transformation allows the system to extract comprehensive spatial and object information from images captured with a narrow FOV, effectively compensating for the limited field of view by adding depth and contextual information through processed visual data.
Data Source
AI summary
A system, apparatus, and method of preventing a collision of a remote-controlled mobile robot are disclosed. The system includes a mobile robot transmitting image data taken by a camera mounted on the mobile robot and moving in accordance with received control data, and a control appliance receiving and analyzing the image data, displaying the analyzed result on a screen, and transmitting the control data to the mobile robot.