activity
20182023
most citedDeconvolutional Networks for Point-Cloud Vehicle Detection and Tracking in Driving Scenarios

27 citations · 33 across the 6 of their papers we have counts for

collaborators

6 papers

cs.RO2023★ 2 cited

Borinot: an open thrust-torque-controlled robot for research on agile aerial-contact motion

Josep Martí-Saumell, Hugo Duarte, Patrick Grosch +3

This paper introduces Borinot, an open-source aerial robotic platform designed to conduct research on hybrid agile locomotion and manipulation using flight and contacts. This platf…

cs.RO2021

WOLF: A modular estimation framework for robotics based on factor graphs

Joan Sola, Joan Vallve, Joaquim Casals +5

This paper introduces WOLF, a C++ estimation framework based on factor graphs and targeted at mobile robotics. WOLF can be used beyond SLAM to handle self-calibration, model identi…

cs.RO2021★ 4 cited

Full-Body Torque-Level Non-linear Model Predictive Control for Aerial Manipulation

Josep Martí-Saumell, Joan Solà, Angel Santamaria-Navarro +1

Non-linear model predictive control (nMPC) is a powerful approach to control complex robots (such as humanoids, quadrupeds, or unmanned aerial manipulators (UAMs)) as it brings imp…

cs.CV2020

High Speed Event Camera TRacking

William Chamorro, Juan Andrade-Cetto, Joan Solà

Event cameras are bioinspired sensors with reaction times in the order of microseconds. This property makes them appealing for use in highly-dynamic computer vision applications. I…

cs.RO2020

Multi-task closed-loop inverse kinematics stability through semidefinite programming

Josep Marti-Saumell, Angel Santamaria-Navarro, Carlos Ocampo-Martinez +1

Today's complex robotic designs comprise in some cases a large number of degrees of freedom, enabling for multi-objective task resolution (e.g., humanoid robots or aerial manipulat…

cs.CV2018★ 27 cited

Deconvolutional Networks for Point-Cloud Vehicle Detection and Tracking in Driving Scenarios

Victor Vaquero, Ivan del Pino, Francesc Moreno-Noguer +3

Vehicle detection and tracking is a core ingredient for developing autonomous driving applications in urban scenarios. Recent image-based Deep Learning (DL) techniques are obtainin…