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Pascual Campoy

7 accepted papers

2024

Exploring Unstructured Environments Using Minimal Sensing on Cooperative Nano-Drones

Pedro Arias-Perez, Alvika Gautam, Miguel Fernández-Cortizas, David Pérez-Saura, Srikanth Saripalli, Pascual Campoy
RA-L 2024

Recent advances have improved autonomous navigation and mapping under payload constraints, but current multi-robot inspection algorithms are unsuitable for nano-drones, due to their need for heavy sensors and high computational resources. To address these challenges, we introduce <italic xmlns:mml="

Cited by 2Source ↗code ↗Scholar ↗
2024

Multi S-Graphs: An Efficient Distributed Semantic-Relational Collaborative SLAM

Miguel Fernández-Cortizas, Hriday Bavle, David Pérez-Saura, Jose Luis Sanchez-Lopez, Pascual Campoy, Holger Voos
RA-L 2024

Collaborative Simultaneous Localization and Mapping (CSLAM) is critical to enable multiple robots to operate in complex environments. Most CSLAM techniques rely on raw sensor measurement or low-level features such as keyframe descriptors, which can lead to wrong loop closures due to the lack of deep

Cited by 18Source ↗code ↗Scholar ↗
2018

A Deep Reinforcement Learning Technique for Vision-Based Autonomous Multirotor Landing on a Moving Platform

Alejandro Rodriguez-Ramos, Carlos Sampedro, Hriday Bavle, Ignacio Gil Moreno, Pascual Campoy
IROS 2018poster

Deep learning techniques for motion control have recently been qualitatively improved, since the successful application of Deep Q- Learning to the continuous action domain in Atari-like games. Based on these ideas, Deep Deterministic Policy Gradients (DDPG) algorithm was able to provide impressive r…

Cited by 68Source ↗Scholar ↗
2018

Image-Based Visual Servoing Controller for Multirotor Aerial Robots Using Deep Reinforcement Learning

Carlos Sampedro, Alejandro Rodriguez-Ramos, Ignacio Gil, Luis Mejias, Pascual Campoy
IROS 2018poster

In this paper, we propose a novel Image-Based Visual Servoing (IBVS) controller for multirotor aerial robots based on a recent deep reinforcement learning algorithm named Deep Deterministic Policy Gradients (DDPG). The proposed RL-IBVS controller is successfully trained in a Gazebo-based simulation…

Cited by 74Source ↗Scholar ↗
2018

Laser-Based Reactive Navigation for Multirotor Aerial Robots using Deep Reinforcement Learning

Carlos Sampedro, Hriday Bavle, Alejandro Rodriguez-Ramos, Paloma de la Puente, Pascual Campoy
IROS 2018poster

Navigation in unknown indoor environments with fast collision avoidance capabilities is an ongoing research topic. Traditional motion planning algorithms rely on precise maps of the environment, where re-adapting a generated path can be highly demanding in terms of computational cost. In this paper,…

Cited by 54Source ↗Scholar ↗
2018

Stereo Visual Odometry and Semantics based Localization of Aerial Robots in Indoor Environments

Hriday Bavle, Stephan Manthe, Paloma de la Puente, Alejandro Rodriguez-Ramos, Carlos Sampedro, Pascual Campoy
IROS 2018poster

In this paper we propose a particle filter localization approach, based on stereo visual odometry (VO) and semantic information from indoor environments, for mini-aerial robots. The prediction stage of the particle filter is performed using the 3D pose of the aerial robot estimated by the stereo VO…

Cited by 18Source ↗Scholar ↗