Autonomous Mobile Robot Escape Control Using Obstacle Position Maps
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Solution Overview
Problem
Autonomous mobile robots face inefficiencies in escaping complex areas due to poor targeting in their escape strategies, leading to reduced user experience and potential damage.
Innovation Solution
The method involves receiving near-field obstacle information from sensors, generating an obstacle position map, and searching for a passable direction based on this map to create an escape path, using collision, lifting, and non-contact sensing information to guide the robot out of trapped scenarios.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If the autonomous mobile robot adopts strategies of moving backward, rotating, and moving forward to escape, then the robot can attempt to escape from trapped situations, but the escape process has poor targeting resulting in low escape efficiency
Solution Approach 1:
The system performs preliminary actions by generating an obstacle position map before escape, identifying passable directions in advance based on sensor data and map analysis, then executes escape along the predetermined path rather than random movements
Solution Approach 2:
The system continuously receives near-field obstacle information from sensors during escape execution, compares real-time sensor data with the predetermined escape path, and adjusts movements based on this feedback to maintain accurate targeting throughout the escape process
Data Source
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AI summary
The present application relates to a control method for an autonomous mobile robot and an autonomous mobile robot. In an automatic working method, near-field obstacle information sent by at least one sensor is received, an obstacle position map around the autonomous mobile robot is generated based on the near-field obstacle information; an escape path is generated in response to receiving the near-field obstacle information multiple times within a limited time or space, wherein generating an escape path includes: searching for a passable direction based on a current position of the autonomous mobile robot and the obstacle position map. By adopting the method, the autonomous mobile robot can quickly escape, improving working efficiency.