233 citations · 874 across the 19 of their papers we have counts for
20 papers
UNSEEN: Uncertainty-aware Navigation via Sparse Estimation in Unknown Environments
Tommaso Faraci, Marco Camurri, Daniele Fontanelli +1
Visual navigation in unknown environments remains a core challenge in mobile robotics, especially for resource-constrained platforms. Most existing approaches rely on loosely coupl…
DigiForest: Digital Analytics and Robotics for Sustainable Forestry
Marco Camurri, Enrico Tomelleri, Matías Mattamala +18
Covering one third of Earth's land surface, forests are vital to global biodiversity, climate regulation, and human well-being. In Europe, forests and woodlands reach approximately…
Deep IMU Bias Inference for Robust Visual-Inertial Odometry with Factor Graphs
Russell Buchanan, Varun Agrawal, Marco Camurri +2
Visual Inertial Odometry (VIO) is one of the most established state estimation methods for mobile platforms. However, when visual tracking fails, VIO algorithms quickly diverge due…
Factor Graph Fusion of Raw GNSS Sensing with IMU and Lidar for Precise Robot Localization without a Base Station
Jonas Beuchert, Marco Camurri, Maurice Fallon
Accurate localization is a core component of a robot's navigation system. To this end, global navigation satellite systems (GNSS) can provide absolute measurements outdoors and, th…
Hilti-Oxford Dataset: A Millimetre-Accurate Benchmark for Simultaneous Localization and Mapping
Lintong Zhang, Michael Helmberger, Lanke Frank Tarimo Fu +4
Simultaneous Localization and Mapping (SLAM) is being deployed in real-world applications, however many state-of-the-art solutions still struggle in many common scenarios. A key ne…
Team CERBERUS Wins the DARPA Subterranean Challenge: Technical Overview and Lessons Learned
Marco Tranzatto, Mihir Dharmadhikari, Lukas Bernreiter +33
This article presents the CERBERUS robotic system-of-systems, which won the DARPA Subterranean Challenge Final Event in 2021. The Subterranean Challenge was organized by DARPA with…
Multi-Camera LiDAR Inertial Extension to the Newer College Dataset
Lintong Zhang, Marco Camurri, David Wisth +1
We present a multi-camera LiDAR inertial dataset of 4.5 km walking distance as an expansion of the Newer College Dataset. The global shutter multi-camera device is hardware synchro…
Learning Inertial Odometry for Dynamic Legged Robot State Estimation
Russell Buchanan, Marco Camurri, Frank Dellaert +1
This paper introduces a novel proprioceptive state estimator for legged robots based on a learned displacement measurement from IMU data. Recent research in pedestrian tracking has…
Balancing the Budget: Feature Selection and Tracking for Multi-Camera Visual-Inertial Odometry
Lintong Zhang, David Wisth, Marco Camurri +1
We present a multi-camera visual-inertial odometry system based on factor graph optimization which estimates motion by using all cameras simultaneously while retaining a fixed over…
Navigating by Touch: Haptic Monte Carlo Localization via Geometric Sensing and Terrain Classification
Russell Buchanan, Jakub Bednarek, Marco Camurri +3
Legged robot navigation in extreme environments can hinder the use of cameras and laser scanners due to darkness, air obfuscation or sensor damage. In these conditions, propriocept…
Learning Camera Performance Models for Active Multi-Camera Visual Teach and Repeat
Matías Mattamala, Milad Ramezani, Marco Camurri +1
In dynamic and cramped industrial environments, achieving reliable Visual Teach and Repeat (VT&R) with a single-camera is challenging. In this work, we develop a robust method for…
Unified Multi-Modal Landmark Tracking for Tightly Coupled Lidar-Visual-Inertial Odometry
David Wisth, Marco Camurri, Sandipan Das +1
We present an efficient multi-sensor odometry system for mobile platforms that jointly optimizes visual, lidar, and inertial information within a single integrated factor graph. Th…
Elastic and Efficient LiDAR Reconstruction for Large-Scale Exploration Tasks
Yiduo Wang, Nils Funk, Milad Ramezani +5
We present an efficient, elastic 3D LiDAR reconstruction framework which can reconstruct up to maximum LiDAR ranges (60 m) at multiple frames per second, thus enabling robot explor…
Haptic Sequential Monte Carlo Localization for Quadrupedal Locomotion in Vision-Denied Scenarios
Russell Buchanan, Marco Camurri, Maurice Fallon
Continuous robot operation in extreme scenarios such as underground mines or sewers is difficult because exteroceptive sensors may fail due to fog, darkness, dirt or malfunction. S…
The Newer College Dataset: Handheld LiDAR, Inertial and Vision with Ground Truth
Milad Ramezani, Yiduo Wang, Marco Camurri +3
In this paper we present a large dataset with a variety of mobile mapping sensors collected using a handheld device carried at typical walking speeds for nearly 2.2 km through New…
Preintegrated Velocity Bias Estimation to Overcome Contact Nonlinearities in Legged Robot Odometry
David Wisth, Marco Camurri, Maurice Fallon
In this paper, we present a novel factor graph formulation to estimate the pose and velocity of a quadruped robot on slippery and deformable terrain. The factor graph introduces a…
Robust Legged Robot State Estimation Using Factor Graph Optimization
David Wisth, Marco Camurri, Maurice Fallon
Legged robots, specifically quadrupeds, are becoming increasingly attractive for industrial applications such as inspection. However, to leave the laboratory and to become useful t…
A Factor Graph Approach to Multi-Camera Extrinsic Calibration on Legged Robots
Andrzej Reinke, Marco Camurri, Claudio Semini
Legged robots are becoming popular not only in research, but also in industry, where they can demonstrate their superiority over wheeled machines in a variety of applications. Eith…
Fast and Continuous Foothold Adaptation for Dynamic Locomotion through CNNs
Octavio Villarreal, Victor Barasuol, Marco Camurri +5
Legged robots can outperform wheeled machines for most navigation tasks across unknown and rough terrains. For such tasks, visual feedback is a fundamental asset to provide robots…
Heuristic Planning for Rough Terrain Locomotion in Presence of External Disturbances and Variable Perception Quality
Michele Focchi, Romeo Orsolino, Marco Camurri +4
The quality of the visual feedback can vary significantly on a legged robot that is meant to traverse unknown and unstructured terrains. The map of the environment, acquired with o…