Desktop Robot Recharging Path Planning with Visual-Beacon Fusion
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Solution Overview
Problem
Current recharging methods for desktop robots are inefficient due to interference from indoor environments, leading to low precision and reduced success rates, as they rely solely on wireless signal positioning which is affected by multipath effects and obstacles, resulting in unstable and inaccurate navigation.
Innovation Solution
A recharging control method that integrates camera-based image feature matching with wireless beacon strength information to construct a grid map, plan and correct the recharging path, and improve navigation accuracy by fusing image features with wireless signal data to reduce interference and enhance precision.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If wireless signal positioning technology is used for recharging guide, then the positioning method has low cost and simple setting, but the positioning precision is low and stability is poor due to multipath effect and shielding
Solution Approach 1:
The patent combines wireless signal positioning with visual positioning technologies to create a hybrid positioning system. The visual positioning module captures images of feature points and calculates position information through image processing, while the wireless positioning module provides complementary data. This merging of multiple positioning methods compensates for the weaknesses of individual methods, achieving both ease of implementation and high precision.
2Measurement precision
If ultrasonic waves are used for positioning, then positioning can be achieved, but the method is greatly affected by multipath effect and non-line-of-sight propagation
Solution Approach 1:
The patent integrates ultrasonic positioning with visual positioning and wireless signal positioning. The visual positioning module uses image processing to identify feature points and calculate positions, which is not affected by multipath effects. This combination allows the system to overcome the limitations of ultrasonic waves in complex environments while maintaining positioning capability.
3Device complexity
If single technology navigation is used, then the navigation system is simple, but accumulated error increases and navigation accuracy decreases
Solution Approach 1:
The patent implements a multi-sensor fusion navigation system that combines inertial navigation, visual positioning, and wireless positioning. Each module operates independently and provides complementary information. The inertial navigation module provides continuous position updates, while visual and wireless modules provide absolute position references to correct accumulated errors, achieving high accuracy without excessive system complexity.
Solution Approach 2:
The system uses feedback mechanisms where positioning results from visual and wireless modules are used to correct and update the inertial navigation data. This feedback loop continuously reduces accumulated errors and maintains navigation accuracy over extended periods.
4Ease of operation
If wireless signal strength is used for positioning, then the method is simple to implement, but the signal is easily interfered and positioning stability is poor
Solution Approach 1:
The patent combines wireless signal positioning with visual positioning that uses image feature matching. The visual positioning provides stable, interference-resistant position information by identifying geometric feature points. This combination maintains the simplicity of wireless positioning while dramatically improving stability through the robustness of visual feature matching.
Data Source
AI summary
A recharging control method of a desktop robot is provided. The desktop robot includes a robot body provided with a camera and a base. The recharging control method includes the following steps. When the robot body of the desktop robot receives a charging instruction, images of the desktop environment are collected, the collected two continuous frames of images are controlled to be subjected to feature matching, the position variation of the robot body is calculated, and then a corresponding grid map is constructed (step A); a wireless beacon modulated and transmitted by the base is received, and initial orientation of the base is analyzed according to strength information of the wireless beacon (step B); a recharging path is planned in combination with the change of the position of the robot body and the initial orientation obtained through analysis (step C); the robot body of the desktop robot is controlled to move along the recharging path (step D); when the strength of the wireless beacon is within a preset threshold range, the collected two continuous frames of images are controlled to be subjected to feature matching, then a vector value of the current position of the robot body is calculated, and further, the base is further searched for completing docking and charging (step E).