activity
20182021
most citedStochastic Motion Planning under Partial Observability for Mobile Robots with Continuous Range Measurements

20 citations · 22 across the 3 of their papers we have counts for

collaborators

8 papers

cs.RO2021

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…

cs.RO20211 cited

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…

cs.RO202020 cited

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…

cs.RO20201 cited

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…

cs.LG2019

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…

math.OC2019

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…