activity
20202024
most citedWhere to Look Next: Learning Viewpoint Recommendations for Informative Trajectory Planning

34 citations · 35 across the 6 of their papers we have counts for

collaborators

7 papers

cs.RO2024

Evaluating Dynamic Environment Difficulty for Obstacle Avoidance Benchmarking

Moji Shi, Gang Chen, Álvaro Serra Gómez +2

Dynamic obstacle avoidance is a popular research topic for autonomous systems, such as micro aerial vehicles and service robots. Accurately evaluating the performance of dynamic ob…

cs.RO2023

Interaction-Aware Sampling-Based MPC with Learned Local Goal Predictions

Walter Jansma, Elia Trevisan, Álvaro Serra-Gómez +1

Motion planning for autonomous robots in tight, interaction-rich, and mixed human-robot environments is challenging. State-of-the-art methods typically separate prediction and plan…

cs.RO2023★ 1 cited

Rule-Based Lloyd Algorithm for Multi-Robot Motion Planning and Control with Safety and Convergence Guarantees

Manuel Boldrer, Alvaro Serra-Gomez, Lorenzo Lyons +3

This paper presents a distributed rule-based Lloyd algorithm (RBL) for multi-robot motion planning and control. The main limitations of the basic Loyd-based algorithm (LB) concern…

cs.RO2023

A Framework for Fast Prototyping of Photo-realistic Environments with Multiple Pedestrians

Sara Casao, Andrés Otero, Álvaro Serra-Gómez +3

Robotic applications involving people often require advanced perception systems to better understand complex real-world scenarios. To address this challenge, photo-realistic and ph…

cs.RO2022

Active Classification of Moving Targets with Learned Control Policies

Álvaro Serra-Gómez, Eduardo Montijano, Wendelin Böhmer +1

In this paper, we consider the problem where a drone has to collect semantic information to classify multiple moving targets. In particular, we address the challenge of computing c…

cs.RO2022★ 34 cited

Where to Look Next: Learning Viewpoint Recommendations for Informative Trajectory Planning

Max Lodel, Bruno Brito, Álvaro Serra-Gómez +3

Search missions require motion planning and navigation methods for information gathering that continuously replan based on new observations of the robot's surroundings. Current met…

cs.RO2020

With Whom to Communicate: Learning Efficient Communication for Multi-Robot Collision Avoidance

Álvaro Serra-Gómez, Bruno Brito, Hai Zhu +2

Decentralized multi-robot systems typically perform coordinated motion planning by constantly broadcasting their intentions as a means to cope with the lack of a central system coo…