Robot Obstacle Tracking Across Detection Blind Zones
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Solution Overview
Problem
Cost constraints limit the installation of sufficient sensors in robots, resulting in narrow detection zones and inability to accurately determine static or dynamic obstacles, leading to unsafe and inefficient path planning.
Innovation Solution
A computer-implemented obstacle detection method using sensor modules like RGBD sensors or RGB sensors with lidar, which extract image features and position information to identify and track obstacles, and estimate their position even in detection blind zones by calculating motion states and movement speeds.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If the robot is equipped with sufficient sensors to expand the detection zone, then the obstacle detection capability is improved, but the cost increases
Solution Approach 1:
The system performs preliminary detection actions by recording obstacle information in detection blind zones before the robot moves. When an obstacle is detected in the current field of view, the system proactively records its position and characteristics in blind zones ahead of potential movement paths, enabling future path planning without requiring additional sensors in those blind zones.
Solution Approach 2:
The system creates a copy of obstacle information in detection blind zones by recording position, type, and motion state data. This virtual copy allows the robot to 'see' obstacles in blind zones through data processing rather than physical sensors, maintaining detection capability while avoiding additional hardware costs.
2Productivity
If the robot clears obstacle information in detection blind zones after a period of time, then the information processing efficiency is improved, but the accuracy of determining static or dynamic obstacles deteriorates
Solution Approach 1:
The system dynamically adjusts the retention and processing of obstacle information based on motion state analysis. By calculating motion states from positional changes over time, the system dynamically determines whether obstacles are static or moving, enabling accurate classification without arbitrary time-based clearing of data.
Solution Approach 2:
The system implements feedback through continuous monitoring of obstacle position changes. By comparing obstacle positions across multiple detection cycles and calculating motion states, the system receives feedback about obstacle behavior, enabling accurate determination of static versus dynamic obstacles while maintaining efficient information processing through structured data management.
3Ease of manufacture
If the robot uses timed clearing of obstacle information in detection blind zones, then the data management simplicity is improved, but the reliability of obstacle detection deteriorates
Solution Approach 1:
The system changes the parameter of obstacle information management from simple time-based clearing to motion-state-based retention. By introducing motion state calculation as a new parameter, the system determines whether to retain or clear obstacle information based on detected movement, improving detection reliability while maintaining manageable data through systematic processing rules.
Data Source
AI summary
The present disclosure provides an obstacle detection method as well as an apparatus and a robot using the same. The method includes: obtaining, through the sensor module, image(s); detecting an obstacle image of an obstacle from the image(s) according to characteristic(s) of the obstacle; extracting image feature(s) of the obstacle; obtaining, through the sensor module, a position of the obstacle; associating the image feature(s) of the obstacle with the position of the obstacle; calculating a motion state a the obstacle based on the position information of the obstacle at different moments; and estimating the position of the obstacle in a detection blind zone of the robot based on the motion state. In such a manner, it is capable of providing more accurate position information of the obstacle in the detection blind zone, which is beneficial to the robot to plan a safe and fast moving path.