59 citations · 221 across the 105 of their papers we have counts for
7 papers · 1 filter
Distributed Assignment with Limited Communication for Multi-Robot Multi-Target Tracking
Yoonchang Sung, Ashish Kumar Budhiraja, Ryan K. Williams +1
We study the problem of tracking multiple moving targets using a team of mobile robots. Each robot has a set of motion primitives to choose from in order to collectively maximize t…
GM-PHD Filter for Searching and Tracking an Unknown Number of Targets with a Mobile Sensor with Limited FOV
Yoonchang Sung, Pratap Tokekar
We study the problem of searching for and tracking a collection of moving targets using a robot with a limited Field-Of-View (FOV) sensor. The actual number of targets present in t…
Online Exploration of an Unknown Region of Interest with a Team of Aerial Robots
Yoonchang Sung, Deeksha Dixit, Pratap Tokekar
In this paper, we study the problem of exploring an unknown Region Of Interest (ROI) with a team of aerial robots. The size and shape of the ROI are unknown to the robots. The obje…
Strategies to Inject Spoofed Measurement Data
Zhongshun Zhang, Lifeng Zhou, Pratap Tokekar
We study the problem of designing false measurement data that is injected to corrupt and mislead the output of a Kalman filter. Unlike existing works that focus on detection and fi…
Resilient Active Target Tracking with Multiple Robots
Lifeng Zhou, Vasileios Tzoumas, George J. Pappas +1
The problem of target tracking with multiple robots consists of actively planning the motion of the robots to track the targets. A major challenge for practical deployments is to m…
Tree Search Techniques for Minimizing Detectability and Maximizing Visibility
Zhongshun Zhang, Yoonchang Sung, Lifeng Zhou +3
We introduce and study the problem of planning a trajectory for an agent to carry out a scouting mission while avoiding being detected by an adversarial guard. This introduces an a…
An Approximation Algorithm for Risk-averse Submodular Optimization
Lifeng Zhou, Pratap Tokekar
We study the problem of incorporating risk while making combinatorial decisions under uncertainty. We formulate a discrete submodular maximization problem for selecting a set using…