Deepan Lobo

New Jersey Institute of Technology | NJIT · Department of Electrical and Computer Engineering

Artificial Intelligence (AI) and Computer Vision (CV) have rapidly permeated various industries, increasing demand for professionals well-versed in these disciplines. In response to this need, this study evaluates the effectiveness of a novel undergraduate course that aims to equip students with foundational AI and CV knowledge and skills. Unlike e...

This work demonstrates distributed motion planning for multi-rotor unmanned aerial vehicle in a windy outdoor environment. The motion planning is modeled as a receding horizon mixed integer nonlinear programming (RH-MINLP) problem. Each quadrotor solves an RH-MINLP to generate its time-optimal speed profile along a minimum snap spline path while sa...

This paper presents a competition-based active learning approach that prepares undergraduate students for careers in the drone industry. The competition-based learning (CBL) approach focuses on preparing students for three key drone industry requirements (1) drone assembly, testing, and validation using commercial off-the-shelf (COTS) parts, (2) si...

This tutorial introduces readers to the use of event cameras with frame-based computer vision algorithms. By the end of the article, readers will be proficient in applying off-the-shelf clustering and tracking algorithms to event camera data.

Motion capture systems are crucial in developing multi-quadrotor systems due to their ability to provide fast and accurate ground truth measurements for tracking and control. This paper presents the implementation details and experimental validation of a relatively low-cost motion-capture system for multi-quadrotor motion planning using an event ca...

The exponentially growing Internet of Things (IoT) market presents compelling opportunities for innovators to develop and create meaningful applications affecting everyday life. This shifting IoT paradigm is placing new demands on educational institutions to train students with IoT-relevant skills. Numerous education researchers continue to documen...

This paper presents a real-time method to detect and track multiple mobile ground robots using event cameras. The method uses density-based spatial clustering of applications with noise (DBSCAN) to detect the robots and a single k-dimensional (k - d) tree to accurately keep track of them as they move in an indoor arena. Robust detections and tracks...

Enabling coordinated motion of multiple quadrotors is an active area of research in the field of small unmanned aerial vehicles (sUAVs). While there are many techniques found in the literature that address the problem, these studies are limited to simulation results and seldom account for wind disturbances. This paper presents the experimental vali...

The exponential growth in the adoption of drones in various industrial applications has created a demand for professionals experienced in designing, programming, operating, and piloting drones. This paper reports on an active learning-based instructional approach that prepares students for careers in the drone industry. The approach focuses on thre...

This paper presents a real-time method to detect and track multiple mobile ground robots using event cameras. The method uses density-based spatial clustering of applications with noise (DBSCAN) to detect the robots and a single k-dimensional (k-d) tree to accurately keep track of them as they move in an indoor arena. Robust detections and tracks a...

Ethereum blockchain is a powerful, open-source technology for creating decentralized and secure information sharing systems. The main contribution of this paper is the experimental validation of an Ethereum blockchain-based software and hardware architecture that enables secure communication for multiple small Unmanned Aerial Vehicles (sUAVs). The...

Wind disturbance presents a formidable challenge to the flight performance of multi-rotor small unmanned aerial vehicles (sUAVs). This paper presents a comprehensive review of techniques for measuring wind speed and airspeed for multi-rotor sUAVs. Three categories of sensing techniques are reviewed: flow sensors, anemometers, and tilt-angle based a...

The sustained growth of the solar energy industry has created the need to formalize solar energy education. This paper elucidates a novel, cloud-based, virtual reality (VR) pedagogical system that provides students with the fundamentals of solar or Photovoltaic (PV) cells, solar (PV) modules, and solar (PV) array installation configurations. The VR...