activity
20222024
most citedGNSS-stereo-inertial SLAM for arable farming

20 citations · 20 across the 7 of their papers we have counts for

collaborators

7 papers

cs.CV2024

Camera Motion Estimation from RGB-D-Inertial Scene Flow

Samuel Cerezo, Javier Civera

In this paper, we introduce a novel formulation for camera motion estimation that integrates RGB-D images and inertial data through scene flow. Our goal is to accurately estimate t…

cs.CV2023

Motion-Bias-Free Feature-Based SLAM

Alejandro Fontan, Javier Civera, Michael Milford

For SLAM to be safely deployed in unstructured real world environments, it must possess several key properties that are not encompassed by conventional benchmarks. In this paper we…

cs.RO2023

Faster Optimization in S-Graphs Exploiting Hierarchy

Hriday Bavle, Jose Luis Sanchez-Lopez, Javier Civera +1

3D scene graphs hierarchically represent the environment appropriately organizing different environmental entities in various layers. Our previous work on situational graphs extend…

cs.RO202320 cited

GNSS-stereo-inertial SLAM for arable farming

Javier Cremona, Javier Civera, Ernesto Kofman +1

The accelerating pace in the automation of agricultural tasks demands highly accurate and robust localization systems for field robots. Simultaneous Localization and Mapping (SLAM)…

cs.RO2023

Graph-based Global Robot Simultaneous Localization and Mapping using Architectural Plans

Muhammad Shaheer, Jose Andres Millan-Romera, Hriday Bavle +3

In this paper, we propose a solution for graph-based global robot simultaneous localization and mapping (SLAM) using architectural plans. Before the start of the robot operation, t…

cs.RO2023

Graph-based Global Robot Localization Informing Situational Graphs with Architectural Graphs

Muhammad Shaheer, Jose Andres Millan-Romera, Hriday Bavle +3

In this paper, we propose a solution for legged robot localization using architectural plans. Our specific contributions towards this goal are several. Firstly, we develop a method…