3.5k citations · 6.3k across the 74 of their papers we have counts for
85 papers
KISS-Matcher: Fast and Robust Point Cloud Registration Revisited
Hyungtae Lim, Daebeom Kim, Gunhee Shin +5
While global point cloud registration systems have advanced significantly in all aspects, many studies have focused on specific components, such as feature extraction, graph-theore…
PyPose v0.6: The Imperative Programming Interface for Robotics
Zitong Zhan, Xiangfu Li, Qihang Li +33
PyPose is an open-source library for robot learning. It combines a learning-based approach with physics-based optimization, which enables seamless end-to-end robot learning. It has…
Aggressive Aerial Grasping using a Soft Drone with Onboard Perception
Samuel Ubellacker, Aaron Ray, James Bern +2
Contrary to the stunning feats observed in birds of prey, aerial manipulation and grasping with flying robots still lack versatility and agility. Conventional approaches using rigi…
VERF: Runtime Monitoring of Pose Estimation with Neural Radiance Fields
Dominic Maggio, Courtney Mario, Luca Carlone
We present VERF, a collection of two methods (VERF-PnP and VERF-Light) for providing runtime assurance on the correctness of a camera pose estimate of a monocular camera without re…
Foundations of Spatial Perception for Robotics: Hierarchical Representations and Real-time Systems
Nathan Hughes, Yun Chang, Siyi Hu +4
3D spatial perception is the problem of building and maintaining an actionable and persistent representation of the environment in real-time using sensor data and prior knowledge.…
Task-Aware Risk Estimation of Perception Failures for Autonomous Vehicles
Pasquale Antonante, Sushant Veer, Karen Leung +3
Safety and performance are key enablers for autonomous driving: on the one hand we want our autonomous vehicles (AVs) to be safe, while at the same time their performance (e.g., co…
Hydra-Multi: Collaborative Online Construction of 3D Scene Graphs with Multi-Robot Teams
Yun Chang, Nathan Hughes, Aaron Ray +1
3D scene graphs have recently emerged as an expressive high-level map representation that describes a 3D environment as a layered graph where nodes represent spatial concepts at mu…
Resilient and Distributed Multi-Robot Visual SLAM: Datasets, Experiments, and Lessons Learned
Yulun Tian, Yun Chang, Long Quang +4
This paper revisits Kimera-Multi, a distributed multi-robot Simultaneous Localization and Mapping (SLAM) system, towards the goal of deployment in the real world. In particular, th…
Multi-Camera Visual-Inertial Simultaneous Localization and Mapping for Autonomous Valet Parking
Marcus Abate, Ariel Schwartz, Xue Iuan Wong +6
Localization and mapping are key capabilities for self-driving vehicles. In this paper, we build on Kimera and extend it to use multiple cameras as well as external (eg wheel) odom…
Vision-Based Terrain Relative Navigation on High-Altitude Balloon and Sub-Orbital Rocket
Dominic Maggio, Courtney Mario, Brett Streetman +2
We present an experimental analysis on the use of a camera-based approach for high-altitude navigation by associating mapped landmarks from a satellite image database to camera ima…
Data-Association-Free Landmark-based SLAM
Yihao Zhang, Odin A. Severinsen, John J. Leonard +2
We study landmark-based SLAM with unknown data association: our robot navigates in a completely unknown environment and has to simultaneously reason over its own trajectory, the po…
A Correct-and-Certify Approach to Self-Supervise Object Pose Estimators via Ensemble Self-Training
Jingnan Shi, Rajat Talak, Dominic Maggio +1
Real-world robotics applications demand object pose estimation methods that work reliably across a variety of scenarios. Modern learning-based approaches require large labeled data…
NeRF-SLAM: Real-Time Dense Monocular SLAM with Neural Radiance Fields
Antoni Rosinol, John J. Leonard, Luca Carlone
We propose a novel geometric and photometric 3D mapping pipeline for accurate and real-time scene reconstruction from monocular images. To achieve this, we leverage recent advances…
Probabilistic Volumetric Fusion for Dense Monocular SLAM
Antoni Rosinol, John J. Leonard, Luca Carlone
We present a novel method to reconstruct 3D scenes from images by leveraging deep dense monocular SLAM and fast uncertainty propagation. The proposed approach is able to 3D reconst…
Loc-NeRF: Monte Carlo Localization using Neural Radiance Fields
Dominic Maggio, Marcus Abate, Jingnan Shi +2
We present Loc-NeRF, a real-time vision-based robot localization approach that combines Monte Carlo localization and Neural Radiance Fields (NeRF). Our system uses a pre-trained Ne…
PyPose: A Library for Robot Learning with Physics-based Optimization
Chen Wang, Dasong Gao, Kuan Xu +34
Deep learning has had remarkable success in robotic perception, but its data-centric nature suffers when it comes to generalizing to ever-changing environments. By contrast, physic…
D-Lite: Navigation-Oriented Compression of 3D Scene Graphs for Multi-Robot Collaboration
Yun Chang, Luca Ballotta, Luca Carlone
For a multi-robot team that collaboratively explores an unknown environment, it is of vital importance that collected information is efficiently shared among robots in order to sup…
Present and Future of SLAM in Extreme Underground Environments
Kamak Ebadi, Lukas Bernreiter, Harel Biggie +28
This paper reports on the state of the art in underground SLAM by discussing different SLAM strategies and results across six teams that participated in the three-year-long SubT co…
Estimation Contracts for Outlier-Robust Geometric Perception
Luca Carlone
Outlier-robust estimation is a fundamental problem and has been extensively investigated by statisticians and practitioners. The last few years have seen a convergence across resea…
A Survey on Active Simultaneous Localization and Mapping: State of the Art and New Frontiers
Julio A. Placed, Jared Strader, Henry Carrillo +4
Active Simultaneous Localization and Mapping (SLAM) is the problem of planning and controlling the motion of a robot to build the most accurate and complete model of the surroundin…
Extracting Zero-shot Common Sense from Large Language Models for Robot 3D Scene Understanding
William Chen, Siyi Hu, Rajat Talak +1
Semantic 3D scene understanding is a problem of critical importance in robotics. While significant advances have been made in simultaneous localization and mapping algorithms, robo…
LOCUS 2.0: Robust and Computationally Efficient Lidar Odometry for Real-Time Underground 3D Mapping
Andrzej Reinke, Matteo Palieri, Benjamin Morrell +4
Lidar odometry has attracted considerable attention as a robust localization method for autonomous robots operating in complex GNSS-denied environments. However, achieving reliable…
Optimal and Robust Category-level Perception: Object Pose and Shape Estimation from 2D and 3D Semantic Keypoints
Jingnan Shi, Heng Yang, Luca Carlone
We consider a category-level perception problem, where one is given 2D or 3D sensor data picturing an object of a given category (e.g., a car), and has to reconstruct the 3D pose a…
Certifiable 3D Object Pose Estimation: Foundations, Learning Models, and Self-Training
Rajat Talak, Lisa Peng, Luca Carlone
We consider a certifiable object pose estimation problem, where -- given a partial point cloud of an object -- the goal is to not only estimate the object pose, but also to provide…