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Matteo Palieri

7 accepted papers

2024

SEEK: Semantic Reasoning for Object Goal Navigation in Real World Inspection Tasks

Muhammad Fadhil Ginting, Sung-Kyun Kim, David Fan, Matteo Palieri, Mykel Kochenderfer, Ali-akbar Agha-mohammadi
RSS 2024poster

This paper addresses the problem of object-goal navigation in autonomous inspections in real-world environments. Object-goal navigation is crucial to enable effective inspections in various settings, often requiring the robot to identify the target object within a large search space. Current object…

Cited by 8Source ↗PDF ↗Scholar ↗
2022

LAMP 2.0: A Robust Multi-Robot SLAM System for Operation in Challenging Large-Scale Underground Environments

Yun Chang, Kamak Ebadi, Christopher E. Denniston, Muhammad Fadhil Ginting, Antoni Rosinol, Andrzej Reinke +6
RA-L 2022

Search and rescue with a team of heterogeneous mobile robots in unknown and large-scale underground environments requires high-precision localization and mapping. This crucial requirement is faced with many challenges in complex and perceptually-degraded subterranean environments, as the onboard per

Cited by 154Source ↗Scholar ↗
2022

LOCUS 2.0: Robust and Computationally Efficient Lidar Odometry for Real-Time 3D Mapping

Andrzej Reinke, Matteo Palieri, Benjamin Morrell, Yun Chang, Kamak Ebadi, Luca Carlone +1
RA-L 2022

Lidar odometry has attracted considerable attention as a robust localization method for autonomous robots operating in complex GNSS-denied environments. However, achieving reliable and efficient performance on heterogeneous platforms in large-scale environments remains an open challenge due to the l

Cited by 86Source ↗Scholar ↗
2021

Corrections to "LOCUS: A Multi-Sensor Lidar-Centric Solution for High-Precision Odometry and 3D Mapping in Real-Time"

Matteo Palieri, Benjamin Morrell, Abhishek Thakur, Kamak Ebadi, Jeremy Nash, Arghya Chatterjee +4
RA-L 2021

Authors Benjamin Morrell, Kamak Ebadi, Jeremy Nash and Aliakbar Agha-mohammadi in the above-named work [ibid., IEEE Robot. Automat. Lett., vol. 6, no. 2, pp. 421–428, Apr. 2020] were incorrectly affiliated with the Polytechnic University of Bari. The correct authors affiliations are reported in the

Cited by 2Source ↗Scholar ↗
2021

LOCUS: A Multi-Sensor Lidar-Centric Solution for High-Precision Odometry and 3D Mapping in Real-Time

Matteo Palieri, Benjamin Morrell, Abhishek Thakur, Kamak Ebadi, Jeremy Nash, Arghya Chatterjee +4
RA-L 2021

A reliable odometry source is a prerequisite to enable complex autonomy behaviour in next-generation robots operating in extreme environments. In this work, we present a high-precision lidar odometry system to achieve robust and real-time operation under challenging perceptual conditions. LOCUS (Lid

Cited by 134Source ↗Scholar ↗
2020

Autonomous Spot: Long-Range Autonomous Exploration of Extreme Environments with Legged Locomotion

Amanda Bouman, Muhammad Fadhil Ginting, Nikhilesh Alatur, Matteo Palieri, David D. Fan, Thomas Touma +5
IROS 2020poster

This paper serves as one of the first efforts to enable large-scale and long-duration autonomy using the Boston Dynamics Spot robot. Motivated by exploring extreme environments, particularly those involved in the DARPA Subterranean Challenge, this paper pushes the boundaries of the state-of-practice…

Cited by 198Source ↗Scholar ↗
2020

LAMP: Large-Scale Autonomous Mapping and Positioning for Exploration of Perceptually-Degraded Subterranean Environments

Kamak Ebadi, Yun Chang, Matteo Palieri, Alex Stephens, Alex Hatteland, Eric Heiden +6
ICRA 2020poster

Simultaneous Localization and Mapping (SLAM) in large-scale, unknown, and complex subterranean environments is a challenging problem. Sensors must operate in off-nominal conditions; uneven and slippery terrains make wheel odometry inaccurate, while long corridors without salient features make extero…

Cited by 210Source ↗Scholar ↗