Chuchu Fan

MIT

収録論文 64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

• ペアシステムを用いた障害発見のためのカバレッジ考慮型能動評価
  能動学習/障害発見2026/8/13

  限られたテスト予算で実世界の障害を効率的に発見するため、プロキシシステムの情報を活用しつつ、実システムの評価結果と組み合わせて障害が起きそうなシナリオを適応的に選択する手法を提案した。

• Safe and Scalable Multi-Drone Payload Transport via CBF-based Reinforcement Learning with Zero-Shot Sim-to-Real Transfer
  2026/7/1
• Scenario Generation for Testing of Autonomous Driving Systems Using Real-World Failure Records
  2026/6/1
• Value Functions for Temporal Logic: Optimal Policies and Safety Filters
  2026/5/1
• Navigating the Clutter: Waypoint-Based Bi-Level Planning for Multi-Robot Systems
  2026/4/1
• Bellman Value Decomposition for Task Logic in Safe Optimal Control
  2026/2/1
• Solving Parameter-Robust Avoid Problems with Unknown Feasibility using Reinforcement Learning
  2026/2/1
• ReFORM: Reflected Flows for On-support Offline RL via Noise Manipulation
  2026/2/1
• Parameter-Robust MPPI for Safe Online Learning of Unknown Parameters
  2026/1/1
• Structured Interfaces for Automated Reasoning with 3D Scene Graphs
  2025/10/1
• Simulation to Rules: A Dual-VLM Framework for Formal Visual Planning
  2025/10/1
• TGPO: Temporal Grounded Policy Optimization for Signal Temporal Logic Tasks
  2025/10/1
• TGPO: Temporal Grounded Policy Optimization for Signal Temporal Logic Tasks
  2025/9/30
• Hierarchical Multi-Agent Reinforcement Learning with Control Barrier Functions for Safety-Critical Autonomous Systems
  2025/7/1
• Language-Grounded Hierarchical Planning and Execution with Multi-Robot 3D Scene Graphs
  2025/6/1
• TeLoGraF: Temporal Logic Planning via Graph-encoded Flow Matching
  2025/5/1
• Collision- and Reachability-Aware Multi-Robot Control with Grounded LLM Planners
  2025/5/1
• AuDeRe: Automated Strategy Decision and Realization in Robot Planning and Control via LLMs
  2025/4/1
• Solving Multi-Agent Safe Optimal Control with Distributed Epigraph Form MARL
  2025/4/1
• Reliable and Efficient Multi-Agent Coordination via Graph Neural Network Variational Autoencoders
  2025/3/1
• Code-as-Symbolic-Planner: Foundation Model-Based Robot Planning via Symbolic Code Generation
  2025/3/1
• Discrete GCBF Proximal Policy Optimization for Multi-agent Safe Optimal Control
  2025/2/1
• Safe Beyond the Horizon: Efficient Sampling-based MPC with Neural Control Barrier Functions
  2025/2/1
• Safety on the Fly: Constructing Robust Safety Filters via Policy Control Barrier Functions at Runtime
  2024/10/1
• Solving Minimum-Cost Reach Avoid using Reinforcement Learning
  2024/10/1
• Failure Prediction from Limited Hardware Demonstrations
  2024/10/1
• Rigid Body Path Planning using Mixed-Integer Linear Programming
  2024/9/1
• Optimization of Multi-Agent Flying Sidekick Traveling Salesman Problem over Road Networks
  2024/8/1
• Scalable Surrogate Verification of Image-based Neural Network Control Systems using Composition and Unrolling
  2024/5/1
• RADIUM: Predicting and Repairing End-to-End Robot Failures using Gradient-Accelerated Sampling
  2024/4/1
• Foundation Models to the Rescue: Deadlock Resolution in Connected Multi-Robot Systems
  2024/4/1
• Efficient Motion Planning for Manipulators with Control Barrier Function-Induced Neural Controller
  2024/4/1
• PRompt Optimization in Multi-Step Tasks (PROMST): Integrating Human Feedback and Heuristic-based Sampling
  2024/2/1
• GCBF+: A Neural Graph Control Barrier Function Framework for Distributed Safe Multi-Agent Control
  2024/1/1
• Almost-Sure Safety Guarantees of Stochastic Zero-Control Barrier Functions Do Not Hold
  2023/12/1
• Learning Safe Control for Multi-Robot Systems: Methods, Verification, and Open Challenges
  2023/11/1
• How to Train Your Neural Control Barrier Function: Learning Safety Filters for Complex Input-Constrained Systems
  2023/10/1
• Signal Temporal Logic Neural Predictive Control
  2023/9/1
• A Bayesian approach to breaking things: efficiently predicting and repairing failure modes via sampling
  2023/9/1
• Scalable Multi-Robot Collaboration with Large Language Models: Centralized or Decentralized Systems?
  2023/9/1
• Neural Network-based Fault Detection and Identification for Quadrotors using Dynamic Symmetry
  2023/9/1
• AutoTAMP: Autoregressive Task and Motion Planning with LLMs as Translators and Checkers
  2023/6/1
• Solving Stabilize-Avoid Optimal Control via Epigraph Form and Deep Reinforcement Learning
  2023/5/1
• Hybrid Systems Neural Control with Region-of-Attraction Planner
  2023/3/1
• ConBaT: Control Barrier Transformer for Safe Policy Learning
  2023/3/1
• Shield Model Predictive Path Integral: A Computationally Efficient Robust MPC Approach Using Control Barrier Functions
  2023/2/1
• Learning-based Motion Planning in Dynamic Environments Using GNNs and Temporal Encoding
  2022/10/1
• Density Planner: Minimizing Collision Risk in Motion Planning with Dynamic Obstacles using Density-based Reachability
  2022/10/1
• Enforcing safety for vision-based controllers via Control Barrier Functions and Neural Radiance Fields
  2022/9/1
• Barrier functions enable safety-conscious force-feedback control
  2022/9/1
• Case Studies for Computing Density of Reachable States for Safe Autonomous Motion Planning
  2022/9/1
• Certifiable Robot Design Optimization using Differentiable Programming
  2022/4/1
• Robust Counterexample-guided Optimization for Planning from Differentiable Temporal Logic
  2022/3/1
• Cooperative Task and Motion Planning for Multi-Arm Assembly Systems
  2022/3/1
• Safe Control with Learned Certificates: A Survey of Neural Lyapunov, Barrier, and Contraction methods
  2022/2/1
• Learning Safe, Generalizable Perception-based Hybrid Control with Certificates
  2022/1/1
• Multi-agent Motion Planning from Signal Temporal Logic Specifications
  2022/1/1
• A Theoretical Overview of Neural Contraction Metrics for Learning-based Control with Guaranteed Stability
  2021/10/1
• Safe Nonlinear Control Using Robust Neural Lyapunov-Barrier Functions
  2021/9/1
• Uncertainty-aware Safe Exploratory Planning using Gaussian Process and Neural Control Contraction Metric
  2021/5/1
• Optimal Mixed Discrete-Continuous Planning for Linear Hybrid Systems
  2021/2/1
• Scalable and Safe Multi-Agent Motion Planning with Nonlinear Dynamics and Bounded Disturbances
  2020/12/1
• Learning Certified Control using Contraction Metric
  2020/11/1
• Reactive motion planning with probabilistic safety guarantees
  2020/11/1