20 citations · 28 across the 5 of their papers we have counts for
9 papers
Energy-Aware, Collision-Free Information Gathering for Heterogeneous Robot Teams
Xiaoyi Cai, Brent Schlotfeldt, Kasra Khosoussi +3
This paper considers the problem of safely coordinating a team of sensor-equipped robots to reduce uncertainty about a dynamical process, where the objective trades off information…
Resilient Active Information Acquisition with Teams of Robots
Brent Schlotfeldt, Vasileios Tzoumas, George J. Pappas
Emerging applications of collaborative autonomy, such as Multi-Target Tracking, Unknown Map Exploration, and Persistent Surveillance, require robots plan paths to navigate an envir…
Non-Monotone Energy-Aware Information Gathering for Heterogeneous Robot Teams
Xiaoyi Cai, Brent Schlotfeldt, Kasra Khosoussi +3
This paper considers the problem of planning trajectories for a team of sensor-equipped robots to reduce uncertainty about a dynamical process. Optimizing the trade-off between inf…
Stochastic Motion Planning under Partial Observability for Mobile Robots with Continuous Range Measurements
Ke Sun, Brent Schlotfeldt, George Pappas +1
In this paper, we address the problem of stochastic motion planning under partial observability, more specifically, how to navigate a mobile robot equipped with continuous range se…
Feedback Enhanced Motion Planning for Autonomous Vehicles
Ke Sun, Brent Schlotfeldt, Stephen Chaves +3
In this work, we address the motion planning problem for autonomous vehicles through a new lattice planning approach, called Feedback Enhanced Lattice Planner (FELP). Existing latt…
Learning Q-network for Active Information Acquisition
Heejin Jeong, Brent Schlotfeldt, Hamed Hassani +3
In this paper, we propose a novel Reinforcement Learning approach for solving the Active Information Acquisition problem, which requires an agent to choose a sequence of actions in…
Optimal Algorithms for Submodular Maximization with Distributed Constraints
Alexander Robey, Arman Adibi, Brent Schlotfeldt +2
We consider a class of discrete optimization problems that aim to maximize a submodular objective function subject to a distributed partition matroid constraint. More precisely, we…
Learning Safe Unlabeled Multi-Robot Planning with Motion Constraints
Arbaaz Khan, Chi Zhang, Shuo Li +6
In this paper, we present a learning approach to goal assignment and trajectory planning for unlabeled robots operating in 2D, obstacle-filled workspaces. More specifically, we tac…
Resilient Active Information Gathering with Mobile Robots
Brent Schlotfeldt, Vasileios Tzoumas, Dinesh Thakur +1
Applications of safety, security, and rescue in robotics, such as multi-robot target tracking, involve the execution of information acquisition tasks by teams of mobile robots. How…