Robot Path Navigation Using Visual Feature Matching
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Solution Overview
Problem
Conventional methods for training robots to navigate along a path are inefficient as they rely on replaying motor commands, which can lead to drift and instability due to variability in motor command translation to physical movement.
Innovation Solution
A method involving a special purpose computing platform that determines a control signal for a robot by comparing input features to training feature sets, using a similarity measure to select appropriate training sets and transform potential control signals into a final control signal, allowing the robot to adapt to navigation tasks.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If motor commands are replayed for robot navigation training, then the robot can be trained to follow a path, but drift and instability occur due to variability in motor command translation
Solution Approach 1:
The system continuously compares current sensor data with stored training data and adjusts motor commands in real-time based on the similarity measure, creating a closed-loop feedback system that corrects drift and maintains stable navigation
Solution Approach 2:
The system dynamically adjusts motor command parameters based on the similarity measure calculated from sensor data comparison, allowing the robot to adapt its movement parameters to maintain stability despite variations in the environment or robot state
2Ease of operation
If conventional motor command replay is used, then training can be performed, but accuracy deteriorates due to drift accumulation
Solution Approach 1:
The system uses continuous feedback by comparing current sensor readings with training data and adjusting motor commands accordingly, preventing accuracy degradation while maintaining ease of operation
Solution Approach 2:
The system pre-processes and stores training sensor data and motor commands during a training phase, then uses this pre-prepared data for comparison during autonomous operation to maintain accuracy without complex real-time processing
Data Source
AI summary
An apparatus and methods for training and/or operating a robotic device to follow a trajectory. A robotic vehicle may utilize a camera and stores the sequence of images of a visual scene seen when following a trajectory during training in an ordered buffer. Motor commands associated with a given image may be stored. During autonomous operation, an acquired image may be compared with one or more images from the training buffer in order to determine the most likely match. An evaluation may be performed in order to determine if the image may correspond to a shifted (e.g., left/right) version of a stored image as previously observed. If the new image is shifted left, right turn command may be issued. If the new image is shifted right then left turn command may be issued.