Robot Re-Localization by Movement Through Similar Environments
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Solution Overview
Problem
Existing robot localization technologies face challenges in achieving accurate pose determination due to uncontrollable drift errors during SLAM processes, especially when robots are moved, suspended, or dragged, leading to inaccurate re-localization.
Innovation Solution
A method where the robot moves from its current position to a new position during the localization process, acquiring more environment information and comparing it with the stored environment map to identify its pose, thereby distinguishing similar regional environments and improving localization accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If the robot stays at the original position for localization, then the localization process is simple and quick, but the localization accuracy is insufficient due to similar regional environments causing multiple possible poses
Solution Approach 1:
The patent transitions from static localization (single position) to dynamic localization (multiple positions along a trajectory). By adding the temporal and spatial dimension of movement, the system collects environment information from multiple viewpoints, which resolves the ambiguity of similar regional environments and improves localization accuracy.
Solution Approach 2:
The system performs preliminary movement along a planned trajectory before final pose determination. This preliminary action of moving to multiple positions and collecting environment information in advance allows the robot to distinguish similar regions and accurately identify its pose in the global map.
2Measurement precision
If the robot moves to a new position during localization, then more environment information is acquired improving accuracy, but the localization time and movement complexity increase
Solution Approach 1:
The patent implements continuous environment information acquisition during the movement process. Instead of discrete sampling, the robot continuously collects data along the trajectory, which improves localization accuracy while minimizing unnecessary停顿 and reducing overall localization time.
Solution Approach 2:
The system employs dynamic localization by moving the robot along a trajectory rather than keeping it static. This dynamic approach allows the robot to gather diverse environment information from multiple positions, improving the ability to distinguish similar regions and achieve accurate pose identification.
3Ease of operation
If SLAM technology is used for autonomous navigation, then the robot can navigate autonomously, but drift errors occur when the robot is moved, suspended, or dragged requiring re-localization
Solution Approach 1:
The patent implements a feedback mechanism where the robot compares environment information collected during movement with the pre-built global map. This feedback loop allows the system to detect drift errors and accurately re-localize by matching current observations with map data, thereby improving localization reliability after unauthorized movements.
Data Source
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AI summary
Provided is a method for localizing a robot. The robot may move from a current position to a new position during the localizing process, more environment information may be acquired during the new movement, and then the acquired environment information is compared with an environment map stored in the robot, which facilitates successfully localizing a pose of the robot in the stored environment map. In addition, during the movement and localization of the robot, environment information at different positions is generally different, so that similar regional environments may be distinguished, and the problem that an accurate pose cannot be obtained because there may be a plurality of similar regional environments when the robot stays at the original position for localizing may be overcome.