Keywords

Computer Vision, Estimation, Kalman Filtering, Unmanned Aircraft Systems, Robotics

Abstract

A real-time visual multiple target tracker is demonstrated onboard a descending multirotor. Measurements of moving ground targets are generated using the Kanade-Lucas-Tomasi (KLT) tracking method. Homography-based image registration is used to align the measurements into the same coordinate frame, allowing for the detection of independently moving objects. The recently developed Recursive-RANSAC algorithm uses the visual measurements to estimate targets in clutter. Altitude-dependent tuning increases track continuity and coverage during the descent of the vehicle. The algorithm requires no operator interaction and increases the situation awareness of the unmanned aerial system. Real-time tracking efficiency is analyzed on GPUs and CPUs. Tracking results are presented and discussed using the MOTA and MOTP metrics.

Document Type

Peer-Reviewed Article

Publication Date

2017-09-25

Language

English

College

Ira A. Fulton College of Engineering and Technology

Department

Electrical and Computer Engineering

University Standing at Time of Publication

Graduate Student

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