233 citations · 341 across the 21 of their papers we have counts for
25 papers · 1 filter
Quadruped Obstacle Avoidance and Footstep Planning with Distributed Low-cost Time-of-Flight Sensors
Giammarco Caroleo, Timothée Mahamoodally, Matteo Manzardo +6
Quadruped robots typically rely on depth cameras and LiDAR sensors to map their local environment. However, these sensors have limited close-range coverage, are relatively expensiv…
Advances, challenges, and opportunities for legged robots
Jonas Frey, Matías Mattamala, Hae-Won Park +5
Humanoid and quadrupedal robots have the potential to revolutionize the way we work, interact, and coexist with intelligent machines. To understand their effects on society and how…
LEXI-SG: Monocular 3D Scene Graph Mapping with Room-Guided Feed-Forward Reconstruction
Christina Kassab, Hyeonjae Gil, Matías Mattamala +2
Scene graphs are becoming a standard representation for robot navigation, providing hierarchical geometric and semantic scene understanding. However, most scene graph mapping metho…
Building Forest Inventories with Autonomous Legged Robots -- System, Lessons, and Challenges Ahead
Matías Mattamala, Nived Chebrolu, Jonas Frey +5
Legged robots are increasingly being adopted in industries such as oil, gas, mining, nuclear, and agriculture. However, new challenges exist when moving into natural, less-structur…
A Finite-State Controller Based Offline Solver for Deterministic POMDPs
Alex Schutz, Yang You, Matias Mattamala +3
Deterministic partially observable Markov decision processes (DetPOMDPs) often arise in planning problems where the agent is uncertain about its environmental state but can act and…
Markerless Aerial-Terrestrial Co-Registration of Forest Point Clouds using a Deformable Pose Graph
Benoit Casseau, Nived Chebrolu, Matias Mattamala +2
For biodiversity and forestry applications, end-users desire maps of forests that are fully detailed, from the forest floor to the canopy. Terrestrial laser scanning and aerial las…
AutoInspect: Towards Long-Term Autonomous Industrial Inspection
Michal Staniaszek, Tobit Flatscher, Joseph Rowell +6
We give an overview of AutoInspect, a ROS-based software system for robust and extensible mission-level autonomy. Over the past three years AutoInspect has been deployed in a varie…
Autonomous Forest Inventory with Legged Robots: System Design and Field Deployment
Matías Mattamala, Nived Chebrolu, Benoit Casseau +5
We present a solution for autonomous forest inventory with a legged robotic platform. Compared to their wheeled and aerial counterparts, legged platforms offer an attractive balanc…
Wild Visual Navigation: Fast Traversability Learning via Pre-Trained Models and Online Self-Supervision
Matías Mattamala, Jonas Frey, Piotr Libera +5
Natural environments such as forests and grasslands are challenging for robotic navigation because of the false perception of rigid obstacles from high grass, twigs, or bushes. In…
SiLVR: Scalable Lidar-Visual Reconstruction with Neural Radiance Fields for Robotic Inspection
Yifu Tao, Yash Bhalgat, Lanke Frank Tarimo Fu +3
We present a neural-field-based large-scale reconstruction system that fuses lidar and vision data to generate high-quality reconstructions that are geometrically accurate and capt…
Online Tree Reconstruction and Forest Inventory on a Mobile Robotic System
Leonard Freißmuth, Matias Mattamala, Nived Chebrolu +3
Terrestrial laser scanning (TLS) is the standard technique used to create accurate point clouds for digital forest inventories. However, the measurement process is demanding, requi…
Evaluation and Deployment of LiDAR-based Place Recognition in Dense Forests
Haedam Oh, Nived Chebrolu, Matias Mattamala +2
Many LiDAR place recognition systems have been developed and tested specifically for urban driving scenarios. Their performance in natural environments such as forests and woodland…
Exosense: A Vision-Based Scene Understanding System For Exoskeletons
Jianeng Wang, Matias Mattamala, Christina Kassab +5
Self-balancing exoskeletons are a key enabling technology for individuals with mobility impairments. While the current challenges focus on human-compliant hardware and control, unl…
Resilient Legged Local Navigation: Learning to Traverse with Compromised Perception End-to-End
Jin Jin, Chong Zhang, Jonas Frey +4
Autonomous robots must navigate reliably in unknown environments even under compromised exteroceptive perception, or perception failures. Such failures often occur when harsh envir…
MEM: Multi-Modal Elevation Mapping for Robotics and Learning
Gian Erni, Jonas Frey, Takahiro Miki +2
Elevation maps are commonly used to represent the environment of mobile robots and are instrumental for locomotion and navigation tasks. However, pure geometric information is insu…
Language-EXtended Indoor SLAM (LEXIS): A Versatile System for Real-time Visual Scene Understanding
Christina Kassab, Matias Mattamala, Lintong Zhang +1
Versatile and adaptive semantic understanding would enable autonomous systems to comprehend and interact with their surroundings. Existing fixed-class models limit the adaptability…
Fast Traversability Estimation for Wild Visual Navigation
Jonas Frey, Matias Mattamala, Nived Chebrolu +3
Natural environments such as forests and grasslands are challenging for robotic navigation because of the false perception of rigid obstacles from high grass, twigs, or bushes. In…
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…
An Efficient Locally Reactive Controller for Safe Navigation in Visual Teach and Repeat Missions
Matías Mattamala, Nived Chebrolu, Maurice Fallon
To achieve successful field autonomy, mobile robots need to freely adapt to changes in their environment. Visual navigation systems such as Visual Teach and Repeat (VT&R) often ass…
AEROS: Adaptive RObust least-Squares for Graph-Based SLAM
Milad Ramezani, Matias Mattamala, Maurice Fallon
In robot localisation and mapping, outliers are unavoidable when loop-closure measurements are taken into account. A single false-positive loop-closure can have a very negative imp…
Scalable and Elastic LiDAR Reconstruction in Complex Environments Through Spatial Analysis
Yiduo Wang, Milad Ramezani, Matias Mattamala +1
This paper presents novel strategies for spawning and fusing submaps within an elastic dense 3D reconstruction system. The proposed system uses spatial understanding of the scanned…
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…
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…
Visual SLAM-based Localization and Navigation for Service Robots: The Pepper Case
Cristopher Gómez, Matías Mattamala, Tim Resink +1
We propose a Visual-SLAM based localization and navigation system for service robots. Our system is built on top of the ORB-SLAM monocular system but extended by the inclusion of w…