UAV Multi-Target Tracking With Feedback-Controlled Grouping
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Solution Overview
Problem
Existing systems face challenges in effectively tracking multiple targets using unmanned aerial vehicles (UAVs) equipped with imaging devices, especially when targets move within their environment, as they struggle to maintain accurate positioning and orientation relative to the UAV.
Innovation Solution
A computer-implemented method and system that identifies multiple targets through imaging devices on UAVs, determines a target group based on target states such as position, size, velocity, and orientation, and controls the UAV to track the target group, utilizing feedback control loops to adjust movement and orientation for precise tracking.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If multiple targets are tracked simultaneously, then tracking coverage is improved, but tracking precision deteriorates
Solution Approach 1:
The system segments the multiple targets into distinct target groups based on spatial proximity and motion characteristics. Each target group is processed independently through dedicated tracking pipelines, allowing the system to maintain high precision for each group while tracking many targets overall. The segmentation is performed by analyzing target states including position, velocity, and orientation to cluster targets that share similar trajectories.
Solution Approach 2:
The system transitions from tracking individual targets in 2D image space to tracking target groups in 3D spatial space by incorporating depth information and spatial relationships. This dimensional expansion allows the system to manage multiple targets more effectively by organizing them into hierarchical groups, thereby maintaining precision while increasing tracking capacity.
2Measurement precision
If the UAV adjusts its position and orientation frequently to track moving targets, then tracking accuracy is improved, but energy consumption increases
Solution Approach 1:
The system performs preliminary analysis of target motion patterns and predicts future target positions using velocity and orientation data. By anticipating target movements, the UAV can plan its trajectory in advance and make smoother, more energy-efficient adjustments rather than reacting frequently and sharply to target movements. This predictive approach reduces the frequency and intensity of UAV maneuvers.
Solution Approach 2:
The system implements a feedback control mechanism that continuously monitors tracking accuracy and adjusts UAV position and orientation only when necessary to maintain precision. The feedback loop evaluates target state changes and determines the minimal required UAV adjustments, avoiding unnecessary maneuvers that would consume additional energy while still maintaining accurate tracking.
Data Source
AI summary
A computer-implemented method for tracking multiple targets includes identifying a plurality of targets based on a plurality of images obtained from an imaging device carried by an unmanned aerial vehicle (UAV) via a carrier, determining a target group comprising one or more targets from the plurality of targets, and controlling at least one of the UAV or the carrier to track the target group.