Nils Wilde

Orcid: 0000-0003-3238-8153

According to our database1, Nils Wilde authored at least 21 papers between 2018 and 2024.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.

Timeline

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Bibliography

2024
Statistically Distinct Plans for Multiobjective Task Assignment.
IEEE Trans. Robotics, 2024

Scalarizing Multi-Objective Robot Planning Problems Using Weighted Maximization.
IEEE Robotics Autom. Lett., 2024

2023
Optimizing Task Waiting Times in Dynamic Vehicle Routing.
IEEE Robotics Autom. Lett., September, 2023

Statistically Distinct Plans for Multi-Objective Task Assignment.
CoRR, 2023

Designing Heterogeneous Robot Fleets for Task Allocation and Sequencing.
Proceedings of the International Symposium on Multi-Robot and Multi-Agent Systems, 2023

Approximation Algorithms for Robot Tours in Random Fields with Guaranteed Estimation Accuracy.
Proceedings of the IEEE International Conference on Robotics and Automation, 2023

A Unified Approach to Optimally Solving Sensor Scheduling and Sensor Selection Problems in Kalman Filtering.
Proceedings of the 62nd IEEE Conference on Decision and Control, 2023

2022
Learning Submodular Objectives for Team Environmental Monitoring.
IEEE Robotics Autom. Lett., 2022

Error-Bounded Approximation of Pareto Fronts in Robot Planning Problems.
Proceedings of the Algorithmic Foundations of Robotics XV, 2022

An Improved Greedy Algorithm for Subset Selection in Linear Estimation.
Proceedings of the European Control Conference, 2022

Do we use the Right Measure? Challenges in Evaluating Reward Learning Algorithms.
Proceedings of the Conference on Robot Learning, 2022

Online Multi-Robot Task Assignment with Stochastic Blockages.
Proceedings of the 61st IEEE Conference on Decision and Control, 2022

Informative Path Planning in Random Fields via Mixed Integer Programming.
Proceedings of the 61st IEEE Conference on Decision and Control, 2022

Scheduling Operator Assistance for Shared Autonomy in Multi-Robot Teams.
Proceedings of the 61st IEEE Conference on Decision and Control, 2022

2021
Learning Control Sets for Lattice Planners from User Preferences.
Proceedings of the Algorithmic Foundations of Robotics XIV, 2021

Learning Reward Functions from Scale Feedback.
Proceedings of the Conference on Robot Learning, 8-11 November 2021, London, UK., 2021

2020
Improving user specifications for robot behavior through active preference learning: Framework and evaluation.
Int. J. Robotics Res., 2020

Active Preference Learning using Maximum Regret.
Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, 2020

Learning User Preferences from Corrections on State Lattices.
Proceedings of the 2020 IEEE International Conference on Robotics and Automation, 2020

2019
Bayesian Active Learning for Collaborative Task Specification Using Equivalence Regions.
IEEE Robotics Autom. Lett., 2019

2018
Learning User Preferences in Robot Motion Planning Through Interaction.
Proceedings of the 2018 IEEE International Conference on Robotics and Automation, 2018


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