Hallway Robot Navigation Using Vanishing Lines to Correct Drift
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Solution Overview
Problem
Robots navigating hallways face challenges due to lack of visual features and measurement drift in location tracking, leading to potential damage to themselves or property.
Innovation Solution
Utilizing vanishing lines detection to determine a robot's heading and centeredness, enabling precise navigation through hallways by employing sensors like cameras, TOF, LIDAR, and sonar to estimate pose and implement correction maneuvers.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Extent of automation
If visual inertial odometry (VIO) is used for location tracking, then the robot can navigate autonomously, but measurement drift occurs leading to incorrect navigation values
Solution Approach 1:
The system continuously monitors the robot's position using vanishing line detection and compares it with the planned path, generating real-time feedback to correct deviations. The vanishing point detection provides continuous positional feedback that compensates for drift accumulation in VIO systems.
Solution Approach 2:
Vanishing lines serve as an intermediary reference system between the robot's self-motion model and the environment. By detecting geometric features (vanishing lines) in the visual scene, the system creates an intermediate reference frame that is more stable and accurate for correcting VIO drift than direct feature matching alone.
2Measurement precision
If the robot navigates tightly in a hallway to avoid obstacles, then navigation precision is improved, but the tight physical constraints make navigation more difficult and risky
Solution Approach 1:
The system performs preliminary vanishing line detection and path planning before executing tight hallway navigation. By pre-calculating the centered path relative to detected vanishing lines and identifying potential hazards in advance, the robot can execute precise maneuvers with reduced real-time computational burden and lower risk.
Solution Approach 2:
The patent replaces complex mechanical sensing and obstacle avoidance systems with vision-based vanishing line detection. Instead of relying on multiple sensors and complex obstacle detection algorithms, the system uses geometric vanishing line features to infer hallway structure and navigate centrally, simplifying the navigation system while maintaining precision.
3Measurement precision
If complex navigation algorithms are used to handle measurement drift, then navigation accuracy is improved, but computational requirements increase
Solution Approach 1:
The system extracts only the essential geometric information (vanishing lines and vanishing points) from the visual scene, discarding redundant data. By focusing computation on detecting and tracking these specific geometric features rather than processing all visual information, the system achieves accurate drift correction with minimal computational energy.
Solution Approach 2:
The system changes the parameter space for navigation from raw pixel coordinates to geometric vanishing line parameters. This transformation simplifies the mathematical model for drift correction, converting complex image processing tasks into simpler geometric computations that require less computational power while maintaining accuracy.
Data Source
AI summary
Methods, systems, and apparatus, including computer programs encoded on computer storage media, for robot navigation. One of the methods includes obtaining one or more images of an area from a robot; detecting two or more lines within the one or more images; identifying at least two of the two or more lines as vanishing lines; determining, using the vanishing lines, a correction maneuver; and controlling the robot to implement the correction maneuver.