activity
20062023
most citedPersistent Robotic Tasks: Monitoring and Sweeping in Changing Environments

242 citations · 391 across the 47 of their papers we have counts for

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Showing 2019Show all

7 papers · 1 filter

cs.MA2019

On Re-Balancing Self-Interested Agents in Ride-Sourcing Transportation Networks

Armin Sadeghi, Stephen L. Smith

This paper focuses on the problem of controlling self-interested drivers in ride-sourcing applications. Each driver has the objective of maximizing its profit, while the ride-sourc…

cs.RO2019

Robotic Coverage for Continuous Mapping Ahead of a Moving Vehicle

Barry Gilhuly, Stephen L. Smith

In this paper we investigate the problem of using a UAV to provide current map information of the environment in front of a moving ground vehicle. We propose a simple coverage plan…

cs.RO2019★ 28 cited

Improving User Specifications for Robot Behavior through Active Preference Learning: Framework and Evaluation

Nils Wilde, Alexandru Blidaru, Stephen L. Smith +1

An important challenge in human-robot interaction (HRI) is enabling non-expert users to specify complex tasks for autonomous robots. Recently, active preference learning has been a…

cs.RO2019

Learning a Lattice Planner Control Set for Autonomous Vehicles

Ryan De Iaco, Stephen L. Smith, Krzysztof Czarnecki

This paper introduces a method to compute a sparse lattice planner control set that is suited to a particular task by learning from a representative dataset of vehicle paths. To do…

cs.RO2019

Computing a Minimal Set of t-Spanning Motion Primitives for Lattice Planners

Alexander Botros, Stephen L. Smith

In this paper we consider the problem of computing an optimal set of motion primitives for a lattice planner. The objective we consider is to compute a minimal set of motion primit…

cs.RO2019

Multi-Robot Routing for Persistent Monitoring with Latency Constraints

Ahmad Bilal Asghar, Stephen L. Smith, Shreyas Sundaram

In this paper we study a multi-robot path planning problem for persistent monitoring of an environment. We represent the areas to be monitored as the vertices of a weighted graph.…