Optical Reflective Light Correction for Robot Obstacle Detection
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Solution Overview
Problem
Autonomous robots often misjudge obstacles due to strong reflective lights from highly reflective surfaces, leading to inaccurate distance calculations and false alarms, as conventional algorithms rely solely on the center of gravity of reflected lights without correcting for erroneous information.
Innovation Solution
A method that captures and analyzes frame images of reflective light signals, corrects characteristics based on previous signals to exclude erroneous information, and calculates confidence levels for transverse reflective lights to confirm object detection, ensuring accurate obstacle avoidance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If a light sensor is used to detect obstacles by sensing reflected detection lights, then the autonomous robot can navigate around the house, but misjudgments occur when receiving lights reflected by highly-reflective walls or floors
Solution Approach 1:
The patent applies feedback by comparing the center of gravity position of reflected lights across multiple frames. The system continuously monitors the center of gravity position and uses historical data to identify abnormal deviations caused by highly reflective surfaces, enabling the robot to correct misjudgments and improve detection reliability while maintaining autonomous navigation capability
Solution Approach 2:
The patent implements preliminary action by pre-establishing a reference center of gravity position from normal reflective surfaces. Before making obstacle detection decisions, the system compares current center of gravity positions against this pre-established reference to identify and eliminate false detections from highly reflective surfaces, ensuring more accurate navigation decisions
2Device complexity
If conventional algorithms rely solely on the center of gravity of reflected lights to make determinations, then the processing is simple, but the distance calculation becomes inaccurate due to strong reflective lights
Solution Approach 1:
The patent transitions from one-dimensional center of gravity calculation to two-dimensional analysis by examining both the position and variation of the center of gravity across multiple frames. This dimensional expansion allows the system to distinguish between normal reflective surfaces and highly reflective surfaces that cause misjudgments, improving distance measurement accuracy without significantly increasing algorithmic complexity
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
Effectively eliminates misjudgments by referencing previous reflective light characteristics to correct current signals, preventing false alarms and ensuring accurate obstacle detection and navigation in highly reflective environments.
Implementation Method 1
a light sensor can be used to detect the obstacles by sensing detection lights emitted by a light source when the detection light is reflected by the obstacle on the navigation path
Data Source
AI summary
A method for eliminating misjudgment of a reflective light applied to an autonomous robot is provided. The autonomous robot includes a driving system and an optical sensing system that includes a light source and a light sensor. The light source emits a transverse linear light as detection light and the light sensor senses reflective light signals from an object that reflects the detection light. In the method, a frame image including the reflective light signals is captured by the light sensor, characteristics of the reflective light signals are analyzed, and the characteristics of the reflective light signals can be corrected based on the characteristics of previous reflective light signals stored in a memory of the autonomous robot in order to exclude abnormal information. The object can be confirmed based on the corrected characteristics of reflective light signals. The misjudgment caused by the abnormal information can therefore be eliminated.