Robot surveillance system
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Solution Overview
Problem
Traditional cleaning robots face challenges in navigating indoor spaces with varying furniture arrangements and obstacles, such as steps and cables, due to their inability to detect subtle changes in the environment, leading to collisions and entanglement issues, and existing solutions like ultrasonic wave sensors are costly and complex.
Innovation Solution
A robot surveillance system that incorporates a light-emitting unit emitting an optical pattern, an image capture unit, and an image processing unit to detect changes in the environment, allowing the robot to avoid collisions and detect moving objects, thereby reducing hardware costs and improving detection precision.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If ultrasonic wave sensors are used to detect obstacles, then the robot can avoid collisions, but the hardware cost increases and installation becomes complicated
Solution Approach 1:
The patent replaces ultrasonic wave sensors with a visual system consisting of a light-emitting unit and image capture unit. The light-emitting unit projects optical patterns (such as grid patterns or laser lines) onto the environment, and the image capture unit captures these patterns. By analyzing the distortion and position of these optical patterns in the captured images, the robot can detect obstacles, steps, and cables without requiring expensive ultrasonic sensors, thus reducing hardware complexity while maintaining collision avoidance capability.
Solution Approach 2:
The patent introduces optical patterns as an intermediary between the robot and the environment. These patterns serve as reference markers that reflect off surfaces and return to the image capture unit. The deformation and position changes of these optical patterns provide information about the environment, enabling the robot to detect obstacles and navigate safely without direct contact sensors, thereby simplifying the hardware system.
2Productivity
If traditional cleaning robots move along preset routes, then they can perform cleaning tasks, but they cannot adapt to changes in furniture arrangement or detect new obstacles
Solution Approach 1:
The patent implements dynamic environmental perception by continuously capturing images with the image capture unit and analyzing optical pattern changes in real-time. The system dynamically updates its understanding of the environment by detecting deformations in optical patterns, allowing the robot to adapt its cleaning path automatically when furniture arrangements change or new obstacles appear, thereby maintaining both cleaning efficiency and environmental adaptability.
Solution Approach 2:
The patent establishes a feedback loop where the image capture unit continuously monitors the environment, the image processing unit analyzes optical pattern changes to detect obstacles and environmental changes, and this information feeds back to the navigation system to adjust the robot's cleaning path in real-time. This closed-loop feedback mechanism enables the robot to maintain high cleaning efficiency while adapting to dynamic environmental changes.
3Device complexity
If the robot uses simple collision avoidance methods, then the hardware cost is low, but the detection precision is insufficient for subtle obstacles like cables
Solution Approach 1:
The patent applies local quality by projecting optical patterns with specific characteristics (such as grid patterns, laser lines, or coded patterns) onto different regions of the environment. The image capture unit captures these patterns, and the image processing unit analyzes local deformations and position changes in the optical patterns to detect subtle obstacles like cables, wires, and edges. This localized optical pattern analysis provides high detection precision for subtle obstacles while keeping the hardware simple and cost-effective.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
The system effectively prevents collisions and entanglements by using optical pattern detection to control the robot's movement, reducing hardware costs and enhancing surveillance capabilities while providing instant warnings for security and surveillance.
Implementation Method 1
each light-emitting unit emits a light beam, which comprises an optical pattern incident on and shown by at least one stationary object or at least one moving object
Implementation Method 2
The optical lens captures an image of the stationary or moving object to cause the photo-sensing device to form a captured image of the optical pattern
Implementation Method 3
The optical lens captures an image of the stationary or moving object to cause the photo-sensing device to form a captured image
Data Source
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AI summary
Disclosed is a robot surveillance system for preventing a robot from falling down or collision by means of dynamic detection of moving object invasion. The system includes a light-emitting unit, an image capture unit, an image processing unit, a turning control unit, and a wireless transceiver unit. The image capture unit combines with an optic pattern to provide a visual module for the moving or surveillance robot. The shape of the optic pattern changes as the robot moves toward the object or pothole, and the image processing unit recognizes the detected object to be standstill, and thus controls the moving direction of the robot to effectively avoid falling or collision. Any moving object in the space is detected by the object motion detection, thereby effectively achieving the goal of spatial surveillance and security.