13 citations · 25 across the 19 of their papers we have counts for
19 papers
ELLIPSE: Evidential Learning for Robust Waypoints and Uncertainties
Zihao Dong, Chanyoung Chung, Dong-Ki Kim +5
Robust waypoint prediction is crucial for mobile robots operating in open-world, safety-critical settings. While Imitation Learning (IL) methods have demonstrated great success in…
World Model Failure Classification and Anomaly Detection for Autonomous Inspection
Michelle Ho, Muhammad Fadhil Ginting, Isaac R. Ward +4
Autonomous inspection robots for monitoring industrial sites can reduce costs and risks associated with human-led inspection. However, accurate readings can be challenging due to o…
Delay-Aware Diffusion Policy: Bridging the Observation-Execution Gap in Dynamic Tasks
Aileen Liao, Dong-Ki Kim, Max Olan Smith +2
As a robot senses and selects actions, the world keeps changing. This inference delay creates a gap of tens to hundreds of milliseconds between the observed state and the state at…
GrndCtrl: Grounding World Models via Self-Supervised Reward Alignment
Haoyang He, Jay Patrikar, Dong-Ki Kim +5
Recent advances in video world modeling have enabled large-scale generative models to simulate embodied environments with high visual fidelity, providing strong priors for predicti…
StageACT: Stage-Conditioned Imitation for Robust Humanoid Door Opening
Moonyoung Lee, Dong Ki Kim, Jai Krishna Bandi +4
Humanoid robots promise to operate in everyday human environments without requiring modifications to the surroundings. Among the many skills needed, opening doors is essential, as…
Enter the Mind Palace: Reasoning and Planning for Long-term Active Embodied Question Answering
Muhammad Fadhil Ginting, Dong-Ki Kim, Xiangyun Meng +10
As robots become increasingly capable of operating over extended periods -- spanning days, weeks, and even months -- they are expected to accumulate knowledge of their environments…
Pixels-to-Graph: Real-time Integration of Building Information Models and Scene Graphs for Semantic-Geometric Human-Robot Understanding
Antonello Longo, Chanyoung Chung, Matteo Palieri +4
Autonomous robots are increasingly playing key roles as support platforms for human operators in high-risk, dangerous applications. To accomplish challenging tasks, an efficient hu…
FALCON: Learning Force-Adaptive Humanoid Loco-Manipulation
Yuanhang Zhang, Yifu Yuan, Prajwal Gurunath +7
Humanoid loco-manipulation holds transformative potential for daily service and industrial tasks, yet achieving precise, robust whole-body control with 3D end-effector force intera…
SayComply: Grounding Field Robotic Tasks in Operational Compliance through Retrieval-Based Language Models
Muhammad Fadhil Ginting, Dong-Ki Kim, Sung-Kyun Kim +4
This paper addresses the problem of task planning for robots that must comply with operational manuals in real-world settings. Task planning under these constraints is essential fo…
UNRealNet: Learning Uncertainty-Aware Navigation Features from High-Fidelity Scans of Real Environments
Samuel Triest, David D. Fan, Sebastian Scherer +1
Traversability estimation in rugged, unstructured environments remains a challenging problem in field robotics. Often, the need for precise, accurate traversability estimation is i…
SEEK: Semantic Reasoning for Object Goal Navigation in Real World Inspection Tasks
Muhammad Fadhil Ginting, Sung-Kyun Kim, David D. Fan +3
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 i…
Low Frequency Sampling in Model Predictive Path Integral Control
Bogdan Vlahov, Jason Gibson, David D. Fan +3
Sampling-based model-predictive controllers have become a powerful optimization tool for planning and control problems in various challenging environments. In this paper, we show h…
FRAME: A Modular Framework for Autonomous Map Merging: Advancements in the Field
Nikolaos Stathoulopoulos, Björn Lindqvist, Anton Koval +2
In this article, a novel approach for merging 3D point cloud maps in the context of egocentric multi-robot exploration is presented. Unlike traditional methods, the proposed approa…
Staircase Localization for Autonomous Exploration in Urban Environments
Jinrae Kim, Sunggoo Jung, Sung-Kyun Kim +2
A staircase localization method is proposed for robots to explore urban environments autonomously. The proposed method employs a modular design in the form of a cascade pipeline co…
Semantic Belief Behavior Graph: Enabling Autonomous Robot Inspection in Unknown Environments
Muhammad Fadhil Ginting, David D. Fan, Sung-Kyun Kim +2
This paper addresses the problem of autonomous robotic inspection in complex and unknown environments. This capability is crucial for efficient and precise inspections in various r…
Towards a Reduced Dependency Framework for Autonomous Unified Inspect-Explore Missions
Vignesh Kottayam Viswanathan, Sumeet Gajanan Satpute, Ali-akbar Agha-mohammadi +1
The task of establishing and maintaining situational awareness in an unknown environment is a critical step to fulfil in a mission related to the field of rescue robotics. Predomin…
Event Camera and LiDAR based Human Tracking for Adverse Lighting Conditions in Subterranean Environments
Mario A. V. Saucedo, Akash Patel, Rucha Sawlekar +4
In this article, we propose a novel LiDAR and event camera fusion modality for subterranean (SubT) environments for fast and precise object and human detection in a wide variety of…
Mars Astrobiological Cave and Internal habitability Explorer (MACIE): A New Frontiers Mission Concept
Charity M. Phillips-Lander, Ali Agha-Mohammadi, J. J. Wynne +20
Martian subsurface habitability and astrobiology can be evaluated via a lava tube cave, without drilling. MACIE addresses two key goals of the Decadal Survey (2013-2022) and three…
Exploration-RRT: A multi-objective Path Planning and Exploration Framework for Unknown and Unstructured Environments
Björn Lindqvist, Ali-akbar Agha-mohammadi, George Nikolakopoulos
This article establishes the Exploration-RRT algorithm: A novel general-purpose combined exploration and pathplanning algorithm, based on a multi-goal Rapidly-Exploring Random Tree…