Autonomous Green Space Robot Sticking Detection With Feedback
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Solution Overview
Problem
Autonomous mobile green space processing robots face challenges in efficiently detecting and avoiding sticking situations, leading to unnecessary energy consumption and logic capacity usage due to the lack of reliable detection methods.
Innovation Solution
A method and system that monitor sticking presumption and confirmation criteria, allowing for a two-stage detection process to confirm sticking and initiate countermeasures only when necessary, utilizing a drive system and sensors to change movement and implement countermeasures like increasing processing height or altering propulsion direction.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If a simple sticking detection method is used, then the detection process is simple, but false positives occur leading to unnecessary energy consumption and logic capacity usage
Solution Approach 1:
The detection process is segmented into two distinct stages: a first stage that monitors initial sticking presumption criteria (simple detection), and a second stage that activates only when presumption criteria are met, monitoring confirmation criteria (comprehensive verification). This segmentation allows the system to maintain low energy consumption during normal operation while providing thorough detection only when necessary, thereby resolving the contradiction between detection simplicity and energy efficiency.
2Device complexity
If a simple sticking detection method is used, then the detection process is simple, but false positives occur leading to unnecessary logic capacity usage
Solution Approach 1:
The automated detection system is divided into two logical stages with different complexity levels. The first stage uses simple presumption criteria monitoring that consumes minimal logic capacity. The second stage, which involves more complex confirmation criteria analysis, is activated only when the first stage detects potential sticking. This segmented approach maintains high automation while optimizing logic capacity utilization.
3Reliability
If sticking countermeasures are initiated frequently, then sticking situations are addressed, but energy consumption increases due to unnecessary operations
Solution Approach 1:
The system implements a feedback mechanism where the outcome of movement change attempts is monitored to determine whether actual sticking occurred. If the movement change succeeds (no sticking confirmed), the system returns to normal operation without initiating energy-consuming countermeasures. If sticking is confirmed, then countermeasures are activated. This feedback-based approach ensures countermeasures are only initiated when truly necessary, maintaining reliability while minimizing energy consumption.
4Measurement precision
If a two-stage detection process is implemented, then detection accuracy improves, but the detection process becomes more complex
Solution Approach 1:
The detection process is segmented into two distinct stages: a first stage that monitors initial sticking presumption criteria (simple detection), and a second stage that activates only when presumption criteria are met, monitoring confirmation criteria (comprehensive verification). This segmentation allows the system to maintain low complexity during normal operation while providing thorough detection only when necessary, thereby resolving the contradiction between detection simplicity and energy efficiency.
Solution Approach 2:
The first stage performs preliminary monitoring of sticking presumption criteria continuously at low complexity. Only when these preliminary criteria are met does the system transition to the second stage with comprehensive confirmation criteria monitoring. This preliminary action approach allows the system to maintain high detection accuracy while keeping the overall process complexity manageable by preparing detection resources in advance but activating them only when needed.
Data Source
AI summary
A method for operating an autonomous mobile green space processing robot, wherein the green space processing robot includes a drive system for propulsion of the green space processing robot. The method includes: a) monitoring whether a sticking presumption criterion is met, wherein the sticking presumption criterion is characteristic of suspected sticking of the green space processing robot; b) if the sticking presumption criterion is met, operating the drive system for a movement change of the green space processing robot and monitoring whether a sticking confirmation criterion is met, wherein the sticking confirmation criterion is that the movement change does not occur; and c) if the sticking confirmation criterion is met, initiating a sticking countermeasure of the green space processing robot.