Robot Obstacle Avoidance Using Multi-Sensor Blind Zone Fusion
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Solution Overview
Problem
Current robot navigation systems face detection blind zones due to limitations in sensor technology, particularly when using multiple sensors, leading to reduced obstacle avoidance efficiency and success rates.
Innovation Solution
A method and system that utilize a processor and multiple ranging sensors to collect and process detection data, including a detection data obtaining module, position obtaining module, determining module, path planning module, and movement controlling module, which projects and combines data from different sensors to plan obstacle-free paths, effectively reducing blind zones.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If multiple ranging sensors are used to detect environmental information, then the robot can obtain more complete obstacle information, but detection blind zones still exist due to sensor technology limitations
Solution Approach 1:
The patent combines data from multiple ranging sensors (laser sensor, depth sensor, ultrasonic sensor) by projecting their detection data onto a unified detection plane. This merging of sensor data allows the robot to overcome individual sensor limitations and reduce detection blind zones through complementary information fusion.
Solution Approach 2:
The patent transforms detection data from different sensor coordinate systems into a unified detection plane coordinate system. This dimensional transformation allows data from sensors with different detection geometries to be integrated, effectively eliminating blind zones by viewing the environment from multiple dimensional perspectives.
2Measurement precision
If a single-line laser sensor is used, then the robot can collect detection data on the horizontal plane, but it cannot detect obstacles outside this plane
Solution Approach 1:
The patent merges detection data from the laser sensor (horizontal plane) with data from depth sensors and ultrasonic sensors (other planes). By projecting all sensor data onto a unified detection plane, the system achieves both precise measurement and comprehensive obstacle detection coverage across multiple spatial planes.
Solution Approach 2:
The unified detection plane serves as a universal coordinate system that can accommodate detection data from multiple sensor types with different detection geometries. This multi-functional approach allows a single processing framework to handle data from sensors operating in different spatial dimensions.
3Speed
If a depth sensor is used for close distance ranging, then the robot can detect obstacles at close range, but it has a large detection blind zone due to smaller vision field
Solution Approach 1:
The patent combines depth sensor data (close range) with laser sensor and ultrasonic sensor data (other ranges). The projection to unified detection plane allows close-range obstacles detected by depth sensors to be integrated with mid-range and far-range data, compensating for the depth sensor's limited vision field.
4Reliability
If an ultrasonic sensor is used, then the robot can detect transparent objects, but it can only collect detection data of a single point which has a small measurement range
Solution Approach 1:
The patent merges ultrasonic sensor data (transparent object detection capability) with laser sensor and depth sensor data (broader measurement range). The unified detection plane projection allows single-point ultrasonic measurements to be integrated with multi-point data from other sensors, achieving both transparent object detection and comprehensive measurement coverage.
Data Source
AI summary
The present disclosure provides an obstacle avoidance method and system for a robot having ranging sensors as well as a robot using the same. The method includes: obtaining detection data collected by the plurality of ranging sensors; obtaining a current position of the robot based on the collected detection data; determining whether historical detection data corresponding to the current position has been stored; planning a movement path of the robot based on the collected detection data and the historical detection data and generating movement path information of the movement path, if the historical detection data corresponding to the current position has been stored; and controlling the robot to move along an obstacle-free path based on the movement path information. The present disclosure can effectively break through the limitation of the sensor technology, reduce the detection blind zone, and effectively improve the obstacle avoidance efficiency of a robot.