7 citations · 15 across the 6 of their papers we have counts for
15 papers
Robot Navigation Anticipative Strategies in Deep Reinforcement Motion Planning
Óscar Gil, Alberto Sanfeliu
The navigation of robots in dynamic urban environments, requires elaborated anticipative strategies for the robot to avoid collisions with dynamic objects, like bicycles or pedestr…
Permutation-Invariant Relational Network for Multi-person 3D Pose Estimation
Nicolas Ugrinovic, Adria Ruiz, Antonio Agudo +2
The recovery of multi-person 3D poses from a single RGB image is a severely ill-conditioned problem due to the inherent 2D-3D depth ambiguity, inter-person occlusions, and body tru…
Single-view 3D Body and Cloth Reconstruction under Complex Poses
Nicolas Ugrinovic, Albert Pumarola, Alberto Sanfeliu +1
Recent advances in 3D human shape reconstruction from single images have shown impressive results, leveraging on deep networks that model the so-called implicit function to learn t…
Effects of a Social Force Model reward in Robot Navigation based on Deep Reinforcement Learning
Óscar Gil Viyuela, Alberto Sanfeliu
In this paper is proposed an inclusion of the Social Force Model (SFM) into a concrete Deep Reinforcement Learning (RL) framework for robot navigation. These types of techniques ha…
Improving Map Re-localization with Deep 'Movable' Objects Segmentation on 3D LiDAR Point Clouds
Victor Vaquero, Kai Fischer, Francesc Moreno-Noguer +2
Localization and Mapping is an essential component to enable Autonomous Vehicles navigation, and requires an accuracy exceeding that of commercial GPS-based systems. Current odomet…
Human-robot Collaborative Navigation Search using Social Reward Sources
Marc Dalmasso, Anaís Garrell, Pablo Jiménez +1
This paper proposes a Social Reward Sources (SRS) design for a Human-Robot Collaborative Navigation (HRCN) task: human-robot collaborative search. It is a flexible approach capable…