Soon-Jo Chung

収録論文 41本 ・ フィジカルAI/ロボット学習

※arXiv著者名で収集。同姓同名の別人の論文が含まれる場合があります。

論文

• Planetary Exploration 3.0: A Roadmap for Software-Defined, Radically Adaptive Space Systems
  2026/4/1
• ContractionPPO: Certified Reinforcement Learning via Differentiable Contraction Layers
  2026/3/1
• Environment-Aware Learning of Smooth GNSS Covariance Dynamics for Autonomous Racing
  2026/2/1
• A Counterfactual Reasoning Framework for Fault Diagnosis in Robot Perception Systems
  2025/9/1
• COFFEE: A Shadow-Resilient Real-Time Pose Estimator for Unknown Tumbling Asteroids using Sparse Neural Networks
  2025/8/1
• MonoTher-Depth: Enhancing Thermal Depth Estimation via Confidence-Aware Distillation
  2025/4/1
• Monte Carlo Tree Search with Spectral Expansion for Planning with Dynamical Systems
  2024/12/1
• Motor Imagery Teleoperation of a Mobile Robot Using a Low-Cost Brain-Computer Interface for Multi-Day Validation
  2024/12/1
• Model Predictive Trees: Sample-Efficient Receding Horizon Planning with Reusable Tree Search
  2024/11/1
• Meta-Learning Augmented MPC for Disturbance-Aware Motion Planning and Control of Quadrotors
  2024/10/1
• MAGIC-VFM: Meta-learning Adaptation for Ground Interaction Control with Visual Foundation Models
  2024/7/1
• Semantics from Space: Satellite-Guided Thermal Semantic Segmentation Annotation for Aerial Field Robots
  2024/3/1
• Caltech Aerial RGB-Thermal Dataset in the Wild
  2024/3/1
• Hierarchical Meta-learning-based Adaptive Controller
  2023/11/1
• Joint-Space Multi-Robot Motion Planning with Learned Decentralized Heuristics
  2023/11/1
• RGB-X Object Detection via Scene-Specific Fusion Modules
  2023/10/1
• CaRT: Certified Safety and Robust Tracking in Learning-based Motion Planning for Multi-Agent Systems
  2023/7/1
• Online Self-Supervised Thermal Water Segmentation for Aerial Vehicles
  2023/7/1
• Unsupervised RGB-to-Thermal Domain Adaptation via Multi-Domain Attention Network
  2022/10/1
• Interstellar Object Accessibility and Mission Design
  2022/10/1
• Neural-Rendezvous: Provably Robust Guidance and Control to Encounter Interstellar Objects
  2022/8/1
• Neural-Fly Enables Rapid Learning for Agile Flight in Strong Winds
  2022/5/1
• Learning-based methods to model small body gravity fields for proximity operations: Safety and Robustness
  2021/12/1
• A Theoretical Overview of Neural Contraction Metrics for Learning-based Control with Guaranteed Stability
  2021/10/1
• Contraction Theory for Nonlinear Stability Analysis and Learning-based Control: A Tutorial Overview
  2021/10/1
• Trajectory Optimization of Chance-Constrained Nonlinear Stochastic Systems for Motion Planning Under Uncertainty
  2021/6/1
• Meta-Adaptive Nonlinear Control: Theory and Algorithms
  2021/6/1
• Neural Tree Expansion for Multi-Robot Planning in Non-Cooperative Environments
  2021/4/1
• Learning-based Adaptive Control using Contraction Theory
  2021/3/1
• Meta-Learning-Based Robust Adaptive Flight Control Under Uncertain Wind Conditions
  2021/3/1
• Learning-based Robust Motion Planning with Guaranteed Stability: A Contraction Theory Approach
  2021/2/1
• Neural-Swarm2: Planning and Control of Heterogeneous Multirotor Swarms using Learned Interactions
  2020/12/1
• Neural Stochastic Contraction Metrics for Learning-based Control and Estimation
  2020/11/1
• Neural Contraction Metrics for Robust Estimation and Control: A Convex Optimization Approach
  2020/6/1
• Robust Controller Design for Stochastic Nonlinear Systems via Convex Optimization
  2020/6/1
• Chance-Constrained Trajectory Optimization for Safe Exploration and Learning of Nonlinear Systems
  2020/5/1
• Adaptive Nonlinear Control of Fixed-Wing VTOL with Airflow Vector Sensing
  2020/3/1
• Neural-Swarm: Decentralized Close-Proximity Multirotor Control Using Learned Interactions
  2020/3/1
• GLAS: Global-to-Local Safe Autonomy Synthesis for Multi-Robot Motion Planning with End-to-End Learning
  2020/2/1
• Neural Lander: Stable Drone Landing Control using Learned Dynamics
  2018/11/1
• Target Assignment in Robotic Networks: Distance Optimality Guarantees and Hierarchical Strategies
  2013/8/1