7 citations · 19 across the 21 of their papers we have counts for
23 papers
M3GD: Multi-Modal Multi-View Geometric Diffusion for Camera--LiDAR Novel View Synthesis
Yang Zhou, Jiuhong Xiao, Shizhao Ye +3
Robotic novel view synthesis (NVS) must recover both visual appearance and metric 3D structure, yet most generative NVS methods rely only on images, overlooking LiDAR, a complement…
OREN-X: Octree Residual Network for Real-Time Multi-Modal Mapping
Zhirui Dai, Qihao Qian, Dinh Minh Nguyen +6
To achieve general-purpose autonomy over long horizons, a robot needs to maintain spatial environment information that supports a variety of tasks: geometry for planning and contro…
When Information is Worth the Risk: Behavioral Valuation for Hazardous Robotic Exploration
Alkesh K. Srivastava, Aamodh Suresh, Carlos Nieto-Granda +1
Hazardous robotic exploration requires robots to map spatial risks, such as unsafe terrain, radiation, fire, mines, or structural damage, while operating where collecting informati…
Meridian: Metric-Semantic Primitive Matching for Cross-View Geo-Localization Beyond Urban Environments
Mason Peterson, Qingyuan Li, Yixuan Jia +4
Successful robot automation requires accurate global localization to support repeatability, task planning, goal specification, and safe operation. However, reliable localization in…
NeuroMesh: A Unified Neural Inference Framework for Decentralized Multi-Robot Collaboration
Yang Zhou, Yash Shetye, Long Quang +8
Deploying learned multi-robot models on heterogeneous robots remains challenging due to hardware heterogeneity, communication constraints, and the lack of a unified execution stack…
B-ActiveSEAL: Scalable Uncertainty-Aware Active Exploration with Tightly Coupled Localization-Mapping
Min-Won Seo, Aamodh Suresh, Carlos Nieto-Granda +1
Active robot exploration requires decision-making processes that integrate localization and mapping under tightly coupled uncertainty. However, managing these interdependent uncert…
Behaviorally Heterogeneous Multi-Agent Exploration Using Distributed Task Allocation
Nirabhra Mandal, Aamodh Suresh, Carlos Nieto-Granda +1
We study a problem of multi-agent exploration with behaviorally heterogeneous robots. Each robot maps its surroundings using SLAM and identifies a set of areas of interest (AoIs) o…
Behaviorally Adaptive Multi-Robot Hazard Localization in Failure-Prone, Communication-Denied Environments
Alkesh K. Srivastava, Aamodh Suresh, Carlos Nieto-Granda
We address the challenge of multi-robot autonomous hazard mapping in high-risk, failure-prone, communication-denied environments such as post-disaster zones, underground mines, cav…
BEASST: Behavioral Entropic Gradient based Adaptive Source Seeking for Mobile Robots
Donipolo Ghimire, Aamodh Suresh, Carlos Nieto-Granda +1
This paper presents BEASST (Behavioral Entropic Gradient-based Adaptive Source Seeking for Mobile Robots), a novel framework for robotic source seeking in complex, unknown environm…
Language-Grounded Hierarchical Planning and Execution with Multi-Robot 3D Scene Graphs
Jared Strader, Aaron Ray, Jacob Arkin +11
In this paper, we introduce a multi-robot system that integrates mapping, localization, and task and motion planning (TAMP) enabled by 3D scene graphs to execute complex instructio…
Air-Ground Collaboration for Language-Specified Missions in Unknown Environments
Fernando Cladera, Zachary Ravichandran, Jason Hughes +6
As autonomous robotic systems become increasingly mature, users will want to specify missions at the level of intent rather than in low-level detail. Language is an expressive and…
NavEX: A Multi-Agent Coverage in Non-Convex and Uneven Environments via Exemplar-Clustering
Donipolo Ghimire, Carlos Nieto-Granda, Solmaz S. Kia
This paper addresses multi-agent deployment in non-convex and uneven environments. To overcome the limitations of traditional approaches, we introduce Navigable Exemplar-Based Disp…
Behavioral Entropy-Guided Dataset Generation for Offline Reinforcement Learning
Wesley A. Suttle, Aamodh Suresh, Carlos Nieto-Granda
Entropy-based objectives are widely used to perform state space exploration in reinforcement learning (RL) and dataset generation for offline RL. Behavioral entropy (BE), a rigorou…
Safe and Dynamically-Feasible Motion Planning using Control Lyapunov and Barrier Functions
Pol Mestres, Carlos Nieto-Granda, Jorge Cortés
This paper considers the problem of designing motion planning algorithms for control-affine systems that generate collision-free paths from an initial to a final destination and ca…
CoPeD-Advancing Multi-Robot Collaborative Perception: A Comprehensive Dataset in Real-World Environments
Yang Zhou, Long Quang, Carlos Nieto-Granda +1
In the past decade, although single-robot perception has made significant advancements, the exploration of multi-robot collaborative perception remains largely unexplored. This inv…
Real-World Deployment of a Hierarchical Uncertainty-Aware Collaborative Multiagent Planning System
Martina Stadler Kurtz, Samuel Prentice, Yasmin Veys +5
We would like to enable a collaborative multiagent team to navigate at long length scales and under uncertainty in real-world environments. In practice, planning complexity scales…
Robotic Exploration using Generalized Behavioral Entropy
Aamodh Suresh, Carlos Nieto-Granda, Sonia Martinez
This work presents and evaluates a novel strategy for robotic exploration that leverages human models of uncertainty perception. To do this, we introduce a measure of uncertainty t…
Distributed Safe Navigation of Multi-Agent Systems using Control Barrier Function-Based Optimal Controllers
Pol Mestres, Carlos Nieto-Granda, Jorge Cortés
This paper proposes a distributed controller synthesis framework for safe navigation of multi-agent systems. We leverage control barrier functions to formulate collision avoidance…
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…
Measuring Multi-Source Redundancy in Factor Graphs
Jesse Milzman, Andre Harrison, Carlos Nieto-Granda +1
Factor graphs are a ubiquitous tool for multi-source inference in robotics and multi-sensor networks. They allow for heterogeneous measurements from many sources to be concurrently…
Kimera-Multi: Robust, Distributed, Dense Metric-Semantic SLAM for Multi-Robot Systems
Yulun Tian, Yun Chang, Fernando Herrera Arias +3
This paper presents Kimera-Multi, the first multi-robot system that (i) is robust and capable of identifying and rejecting incorrect inter and intra-robot loop closures resulting f…
DEDUCE: Diverse scEne Detection methods in Unseen Challenging Environments
Anwesan Pal, Carlos Nieto-Granda, Henrik I. Christensen
In recent years, there has been a rapid increase in the number of service robots deployed for aiding people in their daily activities. Unfortunately, most of these robots require h…
Distributed Mapping with Privacy and Communication Constraints: Lightweight Algorithms and Object-based Models
Siddharth Choudhary, Luca Carlone, Carlos Nieto +3
We consider the following problem: a team of robots is deployed in an unknown environment and it has to collaboratively build a map of the area without a reliable infrastructure fo…