Coverage Robot Obstacle Identification During Avoidance Rotation
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Solution Overview
Problem
Autonomous coverage robots face challenges in navigating through unstructured environments with obstacles, as existing technologies struggle to effectively detect and maneuver around them without continuous human guidance.
Innovation Solution
The method involves controlling the robot's movement by receiving sensor signals, rotating away from obstacles, determining changes in sensor signals, and identifying obstacles based on these changes to navigate safely and efficiently, using proximity sensors and a controller to adjust the robot's path and speed.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Extent of automation
If the robot rotates away from sensed obstacles to avoid them, then the robot can maintain continuous operation without human intervention, but the robot may miss detecting the full extent or type of the obstacle
Solution Approach 1:
The robot performs preliminary actions by rotating away from the obstacle and collecting sensor data before making identification decisions. This allows the robot to gather information about the obstacle's characteristics while maintaining safety distance, resolving the contradiction between autonomous operation and information completeness.
Solution Approach 2:
The system uses feedback from sensor signals to continuously monitor obstacle characteristics. By analyzing changes in sensor signals during rotation and using this feedback to identify obstacle types, the robot maintains autonomous operation while compensating for the limited viewing angle through iterative information gathering.
2Measurement precision
If the robot uses sensor signals to identify obstacles, then the robot can navigate more accurately, but the robot requires complex signal processing and analysis
Solution Approach 1:
The patent replaces complex mechanical obstacle identification systems with sensor-based detection and signal processing. Instead of using complex mechanical sensors or multiple sophisticated detection systems, the robot uses changes in sensor signal strength during rotation to identify obstacles, simplifying the overall system while maintaining detection accuracy.
Solution Approach 2:
The system identifies obstacles by monitoring changes in sensor signal parameters (signal strength) as the robot rotates. By analyzing parameter changes rather than requiring absolute precision measurements from multiple complex sensors, the system achieves accurate obstacle identification with simpler detection equipment.
3Loss of information
If the robot rotates to collect more sensor data about obstacles, then the robot can better identify obstacle types, but the cleaning operation efficiency decreases
Solution Approach 1:
The robot performs partial rotation actions to collect sufficient obstacle information without completing full 360-degree scans. By rotating only enough to detect signal changes that characterize the obstacle, the system gathers necessary identification data while minimizing interruption to cleaning operations, balancing information gathering with productivity.
Data Source
AI summary
A method of navigating an autonomous coverage robot on a floor includes controlling movement of the robot across the floor in a cleaning mode. A sensor signal indicative of an obstacle is received. The robot is rotated away from the sensed obstacle. A change in the received sensor signal during at least a portion of the rotation of the robot away from the sensed obstacle is determined. The sensed obstacle is identified based at least in part on the determined change in the received sensor signal.