activity
20192026
most citedImproving User Specifications for Robot Behavior through Active Preference Learning: Framework and Evaluation

28 citations · 70 across the 16 of their papers we have counts for

collaborators
Showing 2023Show all

5 papers · 1 filter

cs.RO2023★ 1 cited

Statistically Distinct Plans for Multi-Objective Task Assignment

Nils Wilde, Javier Alonso-Mora

We study the problem of finding statistically distinct plans for stochastic planning and task assignment problems such as online multi-robot pickup and delivery (MRPD) when facing…

cs.RO2023★ 1 cited

Designing Heterogeneous Robot Fleets for Task Allocation and Sequencing

Nils Wilde, Javier Alonso-Mora

We study the problem of selecting a fleet of robots to service spatially distributed tasks with diverse requirements within time-windows. The problem of allocating tasks to a fleet…

cs.RO2023

Scalarizing Multi-Objective Robot Planning Problems using Weighted Maximization

Nils Wilde, Stephen L. Smith, Javier Alonso-Mora

When designing a motion planner for autonomous robots there are usually multiple objectives to be considered. However, a cost function that yields the desired trade-off between obj…

cs.RO2023★ 8 cited

Optimizing Task Waiting Times in Dynamic Vehicle Routing

Alexander Botros, Barry Gilhuly, Nils Wilde +3

We study the problem of deploying a fleet of mobile robots to service tasks that arrive stochastically over time and at random locations in an environment. This is known as the Dyn…

math.OC2023

A Unified Approach to Optimally Solving Sensor Scheduling and Sensor Selection Problems in Kalman Filtering

Shamak Dutta, Nils Wilde, Stephen L. Smith

We consider a general form of the sensor scheduling problem for state estimation of linear dynamical systems, which involves selecting sensors that minimize the trace of the Kalman…