Q-Drone is a research-oriented unmanned aerial vehicle (UAV), which provides objective path planning to meet the requirements of critical infrastructure mapping such as the complete and homogeneous quality of structure-from-motion results and object waypoint generation for securing a novel view of anomalies. Q-Drone will provide a novel data-driven capability to use ultra-wideband sensors in cooperation with visual sensors (IR and RGB camera) with augmented positioning using deep convolutional neural networks. We provide a unique benchmark for the research communities, called “Q-Drone UWB benchmark”.
Grant Agency: NSERC CREATE – Data Analytics and Visualization; ORF Infrastructure – Advanced Disaster, Emergency, Rapid Response Simulation (ADERSIM)
ITSC 2020 Paper and Releasing Q-Drone UWB Benchmark - Zahra Arjmandi (2nd year Ph.D. student), Dr. Jungwon Kang and Kunwoo Park (M.Sc. Student graduated in 2020) in the labContinue Reading
Ultra-wideband aided UAV positioning using incremental smoothing with ranges and multilateration - Our paper (“Ultra-wideband aided UAV positioning using incremental smoothing with ranges and multilateration”) was accepted by the IROS 2020 (https://www.iros2020.org/)Continue Reading