Method for controlling Anti-falling of a self-propelled device with a built-in cliff sensor, storage medium and computer device
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Solution Overview
Problem
Self-propelled devices face a risk of falling and damage when their cliff sensors fail or are shielded, as they cannot accurately detect height differences, leading to potential irreparable damage.
Innovation Solution
An environmental map is generated with unreachable regions marked, combining historical trigger records of the cliff sensor to determine a task activity forbidden region, controlling the device to perform tasks outside this region.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a cliff sensor is used to detect height differences, then the device can stop before falling, but the device is vulnerable to sensor failure or shielding
Solution Approach 1:
The system performs preliminary mapping of the environment to identify unreachable regions before tasks are executed. By pre-processing environmental data and marking dangerous areas on maps, the system prepares anti-falling measures in advance, reducing reliance on real-time cliff sensor detection alone.
Solution Approach 2:
The patent introduces map-based unreachable region information as an intermediary layer between the cliff sensor and the driving control. This intermediary provides additional spatial awareness about dangerous areas, complementing the cliff sensor's real-time detection and compensating for its potential failures.
2Device complexity
If the device relies solely on cliff sensor triggering, then the control logic is simple, but the device cannot avoid falling when the sensor fails or is shielded
Solution Approach 1:
The environmental map serves multiple functions: it records unreachable regions for navigation avoidance, stores historical cliff sensor trigger locations, and provides spatial context for task planning. This multi-functional use of the map enhances anti-falling reliability without proportionally increasing system complexity.
Solution Approach 2:
The system incorporates feedback from historical cliff sensor trigger records into the environmental map. By analyzing where the cliff sensor has previously triggered and marking these areas as unreachable regions, the system learns from past experiences and improves future anti-falling performance.
3Reliability
If the device avoids all unreachable regions, then falling risk is reduced, but the device's task execution flexibility is limited
Solution Approach 1:
The system applies different levels of avoidance strictness to different unreachable regions based on their characteristics. Regions marked by historical cliff sensor triggers are treated as high-risk areas requiring strict avoidance, while other unreachable regions may allow more flexible navigation strategies depending on task requirements.
Data Source
AI summary
The present application relates to the technical field of self-propelled devices, and discloses a method for preventing a self-propelled device from falling. The method comprises: determining an environmental map corresponding to an operating environment and a historical trigger record of the cliff sensor in the operating environment based on at least one task execution result of the self-propelled device in the operating environment, wherein the environmental map is marked with an unreachable region; determining a task activity forbidden region for the self-propelled device based on the unreachable region and the historical trigger record; and controlling the self-propelled device to perform a preset task outside the task activity forbidden.