Robot displacement detection method and apparatus, storage medium, and electronic device
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Solution Overview
Problem
Existing technologies fail to effectively detect non-autonomous displacement events of robots, such as movements caused by external forces, which disrupt the robot's position awareness and normal operation.
Innovation Solution
A method and apparatus for robot displacement detection that utilizes the inclination angle change of a robot, determined by the displacement increments of its driving wheels and the distance between them, to identify forced displacements by comparing these changes to a predetermined range, allowing for accurate detection without additional hardware.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional displacement detection methods are used, then the robot can track its position during autonomous movement, but it cannot detect non-autonomous displacement events caused by external forces
Solution Approach 1:
The patent combines multiple existing sensors (odometers on driving wheels, inclination angle sensor) that were already present in the robot into a unified displacement detection system. By merging the data from these sensors through a specific calculation method involving inclination angle changes, the system achieves both autonomous movement tracking and forced displacement detection without adding new hardware.
Solution Approach 2:
The detection method serves multiple functions: it detects autonomous displacement during normal operation and simultaneously detects non-autonomous forced displacements. The same sensor suite and processing algorithm handle both scenarios, making the system universally applicable to different movement types without requiring separate detection mechanisms.
2Reliability
If additional detection hardware is added to detect forced displacements, then detection capability is improved, but device complexity and cost increase
Solution Approach 1:
The robot uses its own existing sensors and structural parameters (wheel displacement, wheel baseline distance, inclination angle) to detect forced displacements. The system essentially detects anomalies in its own operational data without needing external or additional specialized sensors, making the solution self-sufficient and avoiding hardware complexity.
Solution Approach 2:
The patent changes the approach from direct force detection to detecting parameter deviations (inclination angle changes) that result from forced displacement. By monitoring changes in inclination angle combined with wheel displacement data, the system indirectly detects forced displacements through parameter analysis rather than direct measurement, avoiding additional hardware.
3Ease of manufacture
If conventional parameters are used for detection, then no additional hardware cost is incurred, but the ability to detect forced displacements was previously unavailable
Solution Approach 1:
The patent reuses conventional parameters (wheel displacement increments and inclination angle changes) that are already measured during normal robot operation. By applying a specific analytical method to these existing parameters, the system enables forced displacement detection without any additional hardware costs, transforming ordinary operational data into diagnostic information.
Data Source
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AI summary
The present disclosure relates to the technical field of artificial intelligence, and provides a robot displacement detection method, a robot displacement detection apparatus, a computer storage medium and an electronic device. The robot displacement detection method comprises: during the moving process of a robot, acquiring a tilt angle variation of the robot; according to a displacement increment of two drive wheels and the distance between the two drive wheels, determining a tilt angle variation range of the robot not affected by an external force; and, when the tilt angle variation is beyond the tilt angle variation range, determining that the robot is forcibly displaced.