Autonomous Robot Infrared Docking Alignment
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Solution Overview
Problem
Existing robots equipped with rechargeable batteries face challenges in autonomously navigating and docking at charging stations, particularly in indoor environments with limited visibility, requiring expensive hardware and inaccurate location-based analysis.
Innovation Solution
The robot employs a combination of vision-based navigation, depth sensors, and infrared (IR) technology, including IR beam projectors and cameras, to identify and align with a docking station using reflectors or IR LEDs, ensuring precise autonomous docking and charging.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If location-based analysis is used for autonomous docking, then the robot can navigate to the docking station, but the accuracy of docking is insufficient
Solution Approach 1:
The patent replaces complex mechanical vision systems with optical infrared detection. The robot uses an infrared detector to sense IR beams emitted by the docking station, substituting sophisticated camera-based vision hardware with a simpler optical sensing mechanism that achieves superior docking precision.
Solution Approach 2:
The patent introduces infrared beams as an intermediary signal between the docking station and the robot. The docking station emits IR beams that serve as a guidance intermediary, allowing the robot to detect its position and align accurately without requiring complex direct vision processing.
2Reliability
If vision-based navigation is used for autonomous docking, then the robot can identify the docking station, but it requires expensive hardware
Solution Approach 1:
The patent employs inexpensive infrared detectors and simple IR LED beacons instead of expensive vision systems. The infrared detection components are significantly cheaper than camera-based navigation hardware while providing more reliable docking detection, especially in low-light conditions where vision systems fail.
Solution Approach 2:
The patent substitutes expensive mechanical vision systems with a simpler optical infrared detection system. This replacement eliminates the need for complex image processing hardware and algorithms, reducing both cost and complexity while improving reliability through direct optical signal detection.
3Use of energy by moving object
If traditional docking methods are used, then the robot can recharge, but it fails in low-light conditions
Solution Approach 1:
The patent changes the detection parameter from visible light (vision-based) to infrared radiation. This parameter change allows the system to operate independently of ambient visible light conditions, enabling reliable docking and recharging in dark or low-light environments where traditional vision systems cannot function.
Solution Approach 2:
The patent replaces vision-based detection with infrared optical detection. This substitution enables the robot to perceive the docking station through infrared beams that are unaffected by visible light conditions, providing environmental adaptability across all lighting scenarios including complete darkness.
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
This solution enables robots to accurately and autonomously dock at charging stations, even in low-light conditions, without the need for expensive hardware, ensuring reliable battery recharging and efficient operation.
Implementation Method 1
the robot can begin monitoring IR sensors thereon for narrow field IR light beams emitted from the docking station
Implementation Method 2
the IR beam projector can project IR light towards the docking station, and the IR camera can capture an image of the docking station
Implementation Method 3
The docking station may have reflectors (e.g., reflective tape) applied selectively thereto in a particular pattern
Data Source
AI summary
Described herein are technologies pertaining to autonomously docking a mobile robot at a docking station for purposes of recharging batteries of the mobile robot. The mobile robot uses vision-based navigation and a known map of the environment to navigate toward the docking station. Once sufficiently proximate to the docking station, the mobile robot captures infrared images of the docking station, and granularly aligns itself with the docking station based upon the captured infrared images of the docking station. As the robot continues to drive towards the docking station, the robot monitors infrared sensors for infrared beams emitted from the docking station. If the infrared sensors receive the infrared beams, the robot continues to drive forward until the robot successfully docks with the docking station.