Autonomous Robot Localization Using Vision, Triangulation, and Odometry
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Solution Overview
Problem
Autonomous devices, such as mobile robots, face challenges in accurate localization due to the unreliability of visual inputs in dynamic environments and the incremental inaccuracies of odometry-based systems, which can compound location errors over time.
Innovation Solution
The autonomous device employs a multi-system approach, combining a vision system for landmark detection, a triangulation system using signal transmission and reception, and an odometry system to determine its location, with processing devices selecting the most reliable location based on mathematical filters and comparisons to control its movements.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Extent of automation
If visual inputs are used for localization, then the system can operate independently with little user input, but the localization becomes unreliable in dynamic environments or when features are not discernable
Solution Approach 1:
The patent combines multiple localization systems (visual inputs, odometry data, and other sensing systems) into a unified localization framework. The processing device integrates data from these different sources to determine the current location, thereby maintaining autonomous operation while improving reliability in dynamic environments where visual inputs alone may be insufficient.
Solution Approach 2:
The system continuously receives feedback from multiple sensing systems and adjusts the localization estimate accordingly. The processing device evaluates odometry data against visual inputs and other sensor data, using this feedback loop to correct drift and maintain accurate localization even when individual systems become unreliable.
2Productivity
If odometry-based localization is used, then the system can determine location incrementally, but location errors compound with each subsequent localization
Solution Approach 1:
The system uses visual inputs and other sensing systems as feedback to correct odometry drift. The processing device continuously compares the incremental odometry-based location estimates against observations from visual landmarks and other sensors, using this feedback to reset and correct accumulated errors, thereby maintaining long-term accuracy while preserving the speed benefits of incremental localization.
Solution Approach 2:
Visual landmarks and other fixed features serve as intermediary reference points that mediate between odometry steps. When visual features are detected, they provide absolute position references that interrupt the incremental odometry chain, preventing error compounding while allowing the system to maintain high-speed continuous localization.
3Reliability
If multiple localization systems are combined, then reliability and accuracy are improved, but device complexity increases
Solution Approach 1:
The processing device is designed to handle multiple types of input data (visual inputs, odometry data, and data from other sensing systems) through a unified localization algorithm. This multi-functional approach allows the system to integrate diverse data sources without requiring separate processing pipelines for each system, thereby improving reliability while controlling complexity through a universal processing framework.
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 approach enhances the accuracy and reliability of localization by averaging or weighting locations from different systems, reducing errors and improving navigation in dynamic environments.
Implementation Method 1
The one or more processing devices may be configured to determine the second location based on a transmitted signal and a timestamp message corresponding to the transmitted signal. The timestamp message may contain a time that the transmitted signal was received by a remote receiver.
Data Source
AI summary
An example autonomous device is configured to move within a space. The autonomous device includes a first system to detect a first location of the autonomous device within the space, with the first location being based on a first fixed reference; a second system to detect a second location of the autonomous device within the space, with the second location being based on a second fixed reference; and a third system to detect a third location of the autonomous device within the space based on relative movements of the autonomous device. One or more processing devices are configured to select one of the first location or the second location based on reliability of at least one of the first location or the second location, and to control movement of the autonomous device using an estimated location that is based on the third location and the selected one of the first location or the second location.