Search Results for author: Patric Jensfelt

Found 26 papers, 11 papers with code

DUFOMap: Efficient Dynamic Awareness Mapping

2 code implementations3 Mar 2024 Daniel Duberg, Qingwen Zhang, Mingkai Jia, Patric Jensfelt

The dynamic nature of the real world is one of the main challenges in robotics.

Computational Efficiency

DeFlow: Decoder of Scene Flow Network in Autonomous Driving

1 code implementation29 Jan 2024 Qingwen Zhang, Yi Yang, Heng Fang, Ruoyu Geng, Patric Jensfelt

Scene flow estimation determines a scene's 3D motion field, by predicting the motion of points in the scene, especially for aiding tasks in autonomous driving.

Autonomous Driving

Fully Sparse Long Range 3D Object Detection Using Range Experts and Multimodal Virtual Points

no code implementations7 Oct 2023 Ajinkya Khoche, Laura Pereira Sánchez, Nazre Batool, Sina Sharif Mansouri, Patric Jensfelt

3D object detection at long-range is crucial for ensuring the safety and efficiency of self-driving cars, allowing them to accurately perceive and react to objects, obstacles, and potential hazards from a distance.

3D Object Detection Depth Completion +3

Towards a Robust Sensor Fusion Step for 3D Object Detection on Corrupted Data

1 code implementation12 Jun 2023 Maciej K. Wozniak, Viktor Karefjards, Marko Thiel, Patric Jensfelt

Multimodal sensor fusion methods for 3D object detection have been revolutionizing the autonomous driving research field.

3D Object Detection Autonomous Driving +3

RGB-D-Based Categorical Object Pose and Shape Estimation: Methods, Datasets, and Evaluation

1 code implementation19 Jan 2023 Leonard Bruns, Patric Jensfelt

Recently, various methods for 6D pose and shape estimation of objects at a per-category level have been proposed.

A Probabilistic Framework for Visual Localization in Ambiguous Scenes

1 code implementation5 Jan 2023 Fereidoon Zangeneh, Leonard Bruns, Amit Dekel, Alessandro Pieropan, Patric Jensfelt

Visual localization allows autonomous robots to relocalize when losing track of their pose by matching their current observation with past ones.

Variational Inference Visual Localization

SDFEst: Categorical Pose and Shape Estimation of Objects from RGB-D using Signed Distance Fields

1 code implementation11 Jul 2022 Leonard Bruns, Patric Jensfelt

Rich geometric understanding of the world is an important component of many robotic applications such as planning and manipulation.

SDF-based RGB-D Camera Tracking in Neural Scene Representations

no code implementations4 May 2022 Leonard Bruns, Fereidoon Zangeneh, Patric Jensfelt

We consider the problem of tracking the 6D pose of a moving RGB-D camera in a neural scene representation.

FloorGenT: Generative Vector Graphic Model of Floor Plans for Robotics

no code implementations7 Mar 2022 Ludvig Ericson, Patric Jensfelt

Floor plans are the basis of reasoning in and communicating about indoor environments.

On the Evaluation of RGB-D-based Categorical Pose and Shape Estimation

1 code implementation21 Feb 2022 Leonard Bruns, Patric Jensfelt

Recently, various methods for 6D pose and shape estimation of objects have been proposed.

Pose Estimation

UFOMap: An Efficient Probabilistic 3D Mapping Framework That Embraces the Unknown

1 code implementation10 Mar 2020 Daniel Duberg, Patric Jensfelt

In applications where the environment is unknown a-priori, or where only a part of the environment is known, it is important that the 3D model can handle the unknown space efficiently.

Robotics

Skew-Explore: Learn faster in continuous spaces with sparse rewards

no code implementations25 Sep 2019 Xi Chen, Yuan Gao, Ali Ghadirzadeh, Marten Bjorkman, Ginevra Castellano, Patric Jensfelt

In this work, we introduce an exploration approach based on maximizing the entropy of the visited states while learning a goal-conditioned policy.

Adversarial Feature Training for Generalizable Robotic Visuomotor Control

no code implementations17 Sep 2019 Xi Chen, Ali Ghadirzadeh, Mårten Björkman, Patric Jensfelt

Deep reinforcement learning (RL) has enabled training action-selection policies, end-to-end, by learning a function which maps image pixels to action outputs.

Reinforcement Learning (RL) Transfer Learning

Knowledge is Never Enough: Towards Web Aided Deep Open World Recognition

no code implementations4 Jun 2019 Massimiliano Mancini, Hakan Karaoguz, Elisa Ricci, Patric Jensfelt, Barbara Caputo

While today's robots are able to perform sophisticated tasks, they can only act on objects they have been trained to recognize.

Open Set Learning

GCNv2: Efficient Correspondence Prediction for Real-Time SLAM

3 code implementations28 Feb 2019 Jiexiong Tang, Ludvig Ericson, John Folkesson, Patric Jensfelt

In this paper, we present a deep learning-based network, GCNv2, for generation of keypoints and descriptors.

Computational Efficiency

Meta-Learning for Multi-objective Reinforcement Learning

no code implementations8 Nov 2018 Xi Chen, Ali Ghadirzadeh, Mårten Björkman, Patric Jensfelt

Multi-objective reinforcement learning (MORL) is the generalization of standard reinforcement learning (RL) approaches to solve sequential decision making problems that consist of several, possibly conflicting, objectives.

Computational Efficiency Continuous Control +4

Kitting in the Wild through Online Domain Adaptation

no code implementations3 Jul 2018 Massimiliano Mancini, Hakan Karaoguz, Elisa Ricci, Patric Jensfelt, Barbara Caputo

This novel dataset allows for testing the robustness of robot visual recognition algorithms to a series of different domain shifts both in isolation and unified.

Object Recognition Online Domain Adaptation

Detection and Tracking of General Movable Objects in Large 3D Maps

no code implementations22 Dec 2017 Nils Bore, Johan Ekekrantz, Patric Jensfelt, John Folkesson

This paper studies the problem of detection and tracking of general objects with long-term dynamics, observed by a mobile robot moving in a large environment.

Unsupervised Object Discovery and Segmentation of RGBD-images

no code implementations18 Oct 2017 Johan Ekekrantz, Nils Bore, Rares Ambrus, John Folkesson, Patric Jensfelt

In this paper we introduce a system for unsupervised object discovery and segmentation of RGBD-images.

Object Object Discovery +1

Adaptive Cost Function for Pointcloud Registration

no code implementations25 Apr 2017 Johan Ekekrantz, John Folkesson, Patric Jensfelt

In this paper we introduce an adaptive cost function for pointcloud registration.

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