Jul 16, 2024 · We address the problem of computing a finite set of weights whose optimal solutions closely approximate the solution of any other weight vector.

Abstract—Many problems in robotics seek to simultaneously optimize several competing objectives. A conventional approach is to create a single cost function ...

We propose an algorithm that greedily adds the weight vector least-represented by the current set, and provide bounds on the regret. We extend our method to ...

Aug 13, 2024 · We propose an algorithm that greedily adds the weight vector least-represented by the current set, and provide bounds on the regret. We extend ...

From quadrotors delivering packages in urban areas to robot arms moving in confined warehouses, motion planning around obstacles is a core challenge in ...

Fingerprint. Dive into the research topics of 'Regret-based Sampling of Pareto Fronts for Multi-Objective Robot Planning Problems'.

Here solutions are sampled iteratively using equality constraints to force new samples to close gaps in the Pareto-front. Yet, this approach is solving a ...

Sadeghi, J. Alonso-Mora and S. L. Smith. Regret-based Sampling of Pareto Fronts for Multi-Objective Robot Planning Problems, IEEE Transactions on Robotics, 40: ...

Regret-Based Sampling of Pareto Fronts for Multiobjective Robot Planning Problems · Pareto Monte Carlo Tree Search for Multi-Objective Informative Planning.

Regret-based Sampling of Pareto Fronts for Multi-Objective Robot Planning Problems. January 2024 · IEEE Transactions on Robotics. Alexander Botros · Nils Wilde ...