Visual-Laser Odometry for Autonomous Sensor Self-Calibration
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Solution Overview
Problem
Autonomous robots face challenges in maintaining accurate sensor calibration due to natural wear and tear, collisions, and temperature fluctuations, leading to unreliable data from classical odometry units like gyroscopes and accelerometers, which requires frequent human intervention for verification.
Innovation Solution
The implementation of laser and imaging odometry systems that allow robots to determine extrinsic biases in sensors autonomously by comparing image discrepancies between captured images, enabling self-calibration and improved localization capabilities.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If classical odometry units (gyroscopes, accelerometers) are used to measure robot motion, then motion data can be obtained, but the data becomes unreliable due to biases and noise accumulation over time
Solution Approach 1:
The system uses visual feedback from the camera to continuously correct odometry drift. By comparing the visual flow field with predicted motion from odometry sensors, the system generates correction signals that compensate for accumulated errors in gyroscope and accelerometer measurements, maintaining long-term reliability.
Solution Approach 2:
The patent replaces reliance on mechanical odometry sensors (gyroscopes, accelerometers) with an optical measurement system using a camera and image processing. The visual odometry approach computes robot motion directly from sequential image frames, eliminating the drift problem inherent in mechanical sensors.
2Reliability
If sensor calibration is verified frequently by operators to ensure accurate operation, then sensor reliability is maintained, but time consumption increases
Solution Approach 1:
The robot performs self-calibration of its sensors autonomously during normal operation. The visual odometry system continuously monitors and corrects sensor biases using environmental visual features, eliminating the need for manual operator intervention and frequent calibration checks.
Solution Approach 2:
Instead of periodic calibration verification, the system implements continuous calibration maintenance through visual feedback. The calibration process runs continuously during robot operation, constantly adjusting sensor parameters to maintain accuracy without interrupting robot tasks.
3Reliability
If laser and imaging odometry systems are implemented for autonomous calibration, then reliance on classical odometry is reduced, but system complexity increases
Solution Approach 1:
The camera system serves multiple functions: it captures images for visual odometry computation, detects visual features for motion estimation, and provides feedback for sensor calibration. This multi-functionality reduces the need for separate dedicated components, managing complexity while improving reliability.
Solution Approach 2:
The patent combines laser range finder and imaging camera into an integrated odometry system that shares processing resources and coordinate frameworks. By merging these sensing modalities, the system achieves improved localization accuracy without proportionally increasing overall system complexity.
Data Source
AI summary
Systems and methods for laser and imaging odometry for autonomous robots are disclosed herein. According to at least one non-limiting exemplary embodiment, a robot may utilize images captured by a sensor and encoded with a depth parameter to determine its motion and localize itself. The determined motion and localization may then be utilized to verify calibration of the sensor based on a comparison between motion and localization data based on the images and motion and localization data based on data from other sensors and odometry units of the robot.