Autonomous Mobile Robot Behavior Zones for Obstacle Avoidance
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Autonomous mobile robots face challenges in navigating environments with obstacles, leading to potential getting stuck or inefficient cleaning due to lack of effective control over their behavior in response to sensor events.
Innovation Solution
The implementation of behavior control zones, which are defined using sensor data and user input, allowing the robot to initiate specific behaviors such as avoidance or focused cleaning by restricting access to certain areas and modifying its operation based on detected sensor events.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If the autonomous mobile robot autonomously navigates and cleans the environment, then the productivity is improved, but the robot may get stuck or encounter obstacles causing reliability to deteriorate
Solution Approach 1:
The system performs preliminary actions by identifying sensor events and their locations during navigation, then proactively defines behavior control zones before the robot encounters problematic areas. This allows the robot to avoid obstacles and get-stuck situations before they occur, maintaining both productivity and reliability.
Solution Approach 2:
The system uses feedback from sensor events collected during robot operation to dynamically define behavior control zones. The sensor data about obstacles and get-stuck locations is processed and fed back into the navigation system, which then adjusts robot behavior by initiating escape behaviors or avoiding specific zones, thereby improving reliability without sacrificing cleaning productivity.
2Reliability
If the robot initiates escape behavior in response to sensor events, then the reliability is improved by avoiding obstacles, but the productivity deteriorates due to time lost in escape maneuvers
Solution Approach 1:
The system defines behavior control zones in advance based on sensor event history, so when the robot enters these zones, escape behaviors are triggered proactively rather than reactively. This preliminary definition allows the robot to avoid obstacles before encountering them, reducing the need for time-consuming escape maneuvers and maintaining cleaning productivity.
Solution Approach 2:
The behavior control zones are dynamically adjusted based on accumulated sensor data and robot performance. The system learns from past sensor events and modifies the zones to optimize the balance between reliability (avoiding obstacles) and productivity (minimizing escape behaviors). This dynamic adaptation ensures that escape behaviors are only triggered when necessary, preserving cleaning output.
3Adaptability or versatility
If the system defines behavior control zones based on sensor data, then the adaptability is improved by customizing robot behavior, but the device complexity increases due to additional processing requirements
Solution Approach 1:
The system segments the environment into discrete behavior control zones based on sensor event locations and characteristics. Each zone can have its own specific behavior rules, allowing customized robot responses without requiring complex global control logic. This segmentation approach enables adaptability while keeping the control system manageable through modular, location-based decision-making.
Solution Approach 2:
The system applies local quality by defining behavior control zones with specific properties and rules tailored to each location's characteristics. Instead of using a single complex global control algorithm, the system creates simple, location-specific behavior rules that are easy to process. This allows high adaptability through customized behaviors while maintaining low device complexity through simple, localized control logic.
Data Source
AI summary
A method includes receiving sensor data collected by an autonomous mobile robot as the autonomous mobile robot moves about an environment, the sensor data being indicative of sensor events and locations associated with the sensor events. The method includes identifying a subset of the sensor events based on the locations. The method includes providing, to a user computing device, data indicative of a recommended behavior control zone in the environment, the recommended behavior control zone containing a subset of the locations associated with the subset of the sensor events. The method includes defining, in response to a user selection from the user computing device, a behavior control zone such that the autonomous mobile robot initiates a behavior in response to encountering the behavior control zone, the behavior control zone being based on the recommended behavior control zone.