Autonomous Mobile Robot Tracking Through Predicted Target Occlusion
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Solution Overview
Problem
Autonomous mobile robots face challenges in maintaining sight of a moving target when encountering obstacles, leading to potential loss of the target, especially when the obstacle occludes the target's view.
Innovation Solution
The robot employs a system with a target acquisition unit, target movement prediction, obstacle movement prediction, occlusion determination, and a target tracking unit that adjusts the camera's field of view to reacquire the target if it is occluded by an obstacle, using imaging units with adjustable fields of view and omnidirectional cameras to predict and avoid collisions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the robot performs obstacle avoidance operation, then collision with moving obstacle is avoided, but the robot may lose sight of the moving target
Solution Approach 1:
The robot predicts the future positions of both the moving target and moving obstacle before executing avoidance maneuvers. By anticipating where the target will be and planning the avoidance path in advance, the robot can maintain continuous target tracking while safely navigating around obstacles, preventing target loss during avoidance operations
Solution Approach 2:
The robot continuously monitors the relative positions of the target and obstacle, and adjusts the avoidance operation in real-time based on predicted target position. This feedback mechanism ensures that the robot maintains sight of the moving target while dynamically adapting the collision avoidance path
2Reliability
If the robot stops to avoid obstacle, then collision is prevented, but the robot enters deadlock state and loses target
Solution Approach 1:
Instead of static stopping behavior, the robot employs dynamic avoidance maneuvers that adapt to the relative motion between target and obstacle. The robot calculates optimal avoidance paths that maintain forward progress toward the moving target while dynamically adjusting to obstacle positions, preventing deadlock states
Solution Approach 2:
The robot predicts future positions of both target and obstacle to plan avoidance maneuvers in advance, allowing continuous movement toward the target without unnecessary stopping. This predictive approach eliminates deadlock by ensuring the robot maintains approach velocity while safely navigating around obstacles
3Device complexity
If the robot uses fixed field of view, then simple tracking is achieved, but target is occluded by obstacle
Solution Approach 1:
The robot dynamically adjusts the field of view of the imaging unit based on predicted obstacle positions and target location. When an obstacle is predicted to occlude the target, the system automatically modifies the field of view parameters to maintain target visibility, balancing system simplicity with effective target tracking
Solution Approach 2:
The field of view adjustment acts as an intermediary mechanism between the obstacle detection system and the target tracking function. By dynamically modifying the imaging parameters based on obstacle predictions, the system maintains target visibility without requiring additional sensors or complex hardware
Data Source
AI summary
An autonomous mobile robot includes a target acquisition unit which acquires a target by using an image obtained by an imaging unit whose field of view is able to be changed, a target movement prediction unit which predicts the destination of the target by using the image of the target, an obstacle movement prediction unit which predicts the destination of an obstacle by using an image of the obstacle, an occlusion determination unit which determines whether or not the target is occluded by the obstacle from result of the prediction by the target movement prediction unit and result of the prediction by the obstacle movement prediction unit, and a target tracking unit which changes the field of view of the imaging unit so that the area of the target coming into the field of view increases in the case where it is determined that at least a part of the target is occluded by the obstacle.