Robot Visual Localization with Adaptive Deceleration on Uneven Surfaces
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Solution Overview
Problem
Robots with autonomous localization and navigation functions face challenges in accurately localizing their position on uneven surfaces, such as cobblestone pavements, leading to failed image capture and navigation route planning, which affects user experience.
Innovation Solution
A localization method where the robot decelerates after determining localization through images fails, allowing it to perform localization during deceleration until successful, using velocity curves like cosine, sinusoidal, trapezoidal, or S-shaped to adjust speed and ensure accurate positioning.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If the robot moves at normal speed on uneven surfaces, then the robot can maintain its driving efficiency, but the image collecting device will be in exposure state for a long time causing blurry images and localization failure
Solution Approach 1:
The robot dynamically adjusts its driving speed based on localization success. When localization fails, the robot automatically decelerates to allow the image collecting device to capture clear images. This dynamic speed adjustment resolves the contradiction by making speed adaptive rather than fixed, allowing the system to maintain productivity when possible while ensuring localization reliability when needed.
Solution Approach 2:
The system implements a feedback loop where localization results are used to control subsequent driving behavior. The localization module provides feedback to the control module, which then adjusts the driving speed accordingly. This closed-loop control ensures that the robot responds to localization conditions in real-time, resolving the contradiction between maintaining speed and ensuring accurate localization.
2Measurement precision
If the robot decelerates to perform localization successfully, then the localization accuracy is improved, but the task completion time increases
Solution Approach 1:
The robot applies partial deceleration rather than complete stopping. The control module adjusts speed to a lower but non-zero value, providing just enough reduction to enable clear image capture and successful localization, while minimizing the time loss. This partial action resolves the contradiction by applying the minimum necessary deceleration to achieve localization accuracy.
Solution Approach 2:
The robot performs periodic localization checks during driving and only decelerates when localization failure is detected. This periodic approach allows the robot to maintain normal speed during successful localization periods, reducing overall time loss while ensuring accuracy when needed. The system alternates between normal operation and localized deceleration based on real-time conditions.
Data Source
AI summary
This application relates to the field of visual navigation technology, and discloses a localization method, apparatus, robot and computer storage medium. The localization method is applied to a robot having an autonomous location and navigation function. The localization method includes: determining that localization through an image of surrounding environment fails in a process of driving to a preset distance, and controlling the robot to decelerate and perform localization through an image of surrounding environment in a process of deceleration until the localization succeeds. The localization method enables the robot to reasonably adjust its running velocity in accordance with the environment during driving, thereby accurately localizing the location where the robot is located.