Mobile Robot Hazard-Adaptive Tilt Control for Coverage and Reliability
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Solution Overview
Problem
Mobile robots face challenges in maximizing coverage while minimizing the risk of encountering hazards such as getting stuck or experiencing over-tilt events while navigating obstacles, which often require human intervention.
Innovation Solution
The mobile robot stores an environment map and data on previously encountered hazards, reducing the tilt threshold in areas where hazards have been detected, allowing it to navigate more cautiously in these areas while maintaining coverage.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Area of stationary object
If the mobile robot increases manoeuvrability over obstacles to maximise coverage, then the coverage is improved, but the risk of encountering hazards such as getting stuck or over-tilt events increases
Solution Approach 1:
The robot dynamically adjusts the tilt threshold parameter based on its location in the environment map. When navigating in hazard-free areas, a higher tilt threshold allows aggressive manoeuvring for maximum coverage. When approaching previously identified hazard areas, the threshold is reduced to prevent hazardous events, creating a dynamic adaptation of robot behavior to environmental context
Solution Approach 2:
The environment map incorporates localized hazard information at specific geographic locations. The robot applies different tilt thresholds locally depending on whether it is in a hazard area or a safe area, rather than using a uniform threshold throughout the entire environment. This allows aggressive navigation in safe zones while exercising caution in problematic zones
2Reliability
If the mobile robot reduces the tilt threshold to avoid hazards, then the reliability is improved, but the coverage and maneuverability are reduced
Solution Approach 1:
The tilt threshold is not statically reduced throughout the entire environment but is dynamically adjusted based on the robot's current location relative to hazard areas in the environment map. This dynamic adjustment allows the robot to maintain high coverage in safe areas while only reducing the threshold locally when necessary for safety
Solution Approach 2:
The robot applies the reduced tilt threshold only in specific local regions where hazards have been previously identified and stored in the environment map. In all other areas outside these hazard zones, the robot maintains the higher original tilt threshold, thereby preserving maximum maneuverability and coverage in safe regions
3Reliability
If the mobile robot requires human intervention to recover from hazards, then the reliability is improved through user control, but the productivity and autonomy are reduced
Solution Approach 1:
The robot performs preliminary actions by storing hazard information in the environment map during and after hazard events. This pre-processing of hazard data allows the robot to proactively adjust its navigation behavior in advance of encountering the same hazards again, preventing recurrence without requiring human intervention
Solution Approach 2:
The system implements feedback by detecting when the robot encounters a hazard, storing this information in the environment map, and then using this stored information to modify future navigation decisions. This closed-loop learning enables the robot to improve its hazard avoidance autonomously over time without human input
Data Source
AI summary
A method of controlling a mobile robot capable of carrying out an operation within an environment, the method including: storing an environment map in a memory, the environment map including data to enable the robot to navigate the environment; further storing in the memory data corresponding to one or more hazard areas encountered by the mobile robot during previous operations; and reducing a tilt threshold of the robot when the mobile robot is navigating within an area of the environment that corresponds to a previously encountered hazard area.