Copertina

Confidence-Aware Learning Optimal Terminal Guidance via Gaussian Process Regression

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autori principali:	Wang, Han, Chen, Donghe, Zheng, Tengjie, Cheng, Lin, Gong, Shengping
Natura:	Preprint
Pubblicazione:	2025
Soggetti:	Systems and Control
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

Recursive Gaussian Process State Space Model
di: Zheng, Tengjie, et al.
Pubblicazione: (2024)

Sparse Kalman Identification for Partially Observable Systems via Adaptive Bayesian Learning
di: Mei, Jilan, et al.
Pubblicazione: (2025)

Recursive Inference for Heterogeneous Multi-Output GP State-Space Models with Arbitrary Moment Matching
di: Zheng, Tengjie, et al.
Pubblicazione: (2025)

Learning-Based Stable Optimal Control for Infinite-Time Nonlinear Regulation Problems
di: Wang, Han, et al.
Pubblicazione: (2025)

Learning-Based Stable Optimal Guidance for Spacecraft Close-Proximity Operations
di: Wang, Kun, et al.
Pubblicazione: (2025)

Terminal Soft Landing Guidance Law Using Analytic Gravity Turn Trajectory
di: Han, Seungyeop, et al.
Pubblicazione: (2024)

Stability Enhancement in Reinforcement Learning via Adaptive Control Lyapunov Function
di: Chen, Donghe, et al.
Pubblicazione: (2025)

Error Distribution Smoothing:Advancing Low-Dimensional Imbalanced Regression
di: Chen, Donghe, et al.
Pubblicazione: (2025)

Resource-Efficient Cooperative Online Scalar Field Mapping via Distributed Sparse Gaussian Process Regression
di: Ding, Tianyi, et al.
Pubblicazione: (2023)

Computation-Aware Learning for Stable Control with Gaussian Process
di: Cao, Wenhan, et al.
Pubblicazione: (2024)

Privacy-Preserving Fully Distributed Gaussian Process Regression
di: Jang, Yeongjun, et al.
Pubblicazione: (2025)

Gaussian Processes with Noisy Regression Inputs for Dynamical Systems
di: Wolff, Tobias M., et al.
Pubblicazione: (2024)

A Local Gaussian Process Regression Approach to Frequency Response Function Estimation
di: Fang, Xiaozhu, et al.
Pubblicazione: (2024)

Optimal Impact Angle Guidance via First-Order Optimization under Nonconvex Constraints
di: Park, Gyubin, et al.
Pubblicazione: (2023)

Solar-Sail Deep Space Trajectory Optimization Using Successive Convex Programming
di: Song, Yu, et al.
Pubblicazione: (2019)

Formal Verification of Unknown Dynamical Systems via Gaussian Process Regression
di: Skovbekk, John, et al.
Pubblicazione: (2021)

Traffic-Aware Eco-Driving Control in CAVs via Learning-based Terminal Cost Model
di: Ozkan, Mehmet Fatih, et al.
Pubblicazione: (2025)

Learning-Based Design of Off-Policy Gaussian Controllers: Integrating Model Predictive Control and Gaussian Process Regression
di: Tekumatla, Shiva Kumar, et al.
Pubblicazione: (2024)

Recursive Gaussian Process Regression with Integrated Monotonicity Assumptions for Control Applications
di: Husmann, Ricus, et al.
Pubblicazione: (2025)

Experiment Design with Gaussian Process Regression with Applications to Chance-Constrained Control
di: Anderson, Sean, et al.
Pubblicazione: (2025)

Reinforcement Learning Based Symbolic Regression for Load Modeling
di: Lin, Ding, et al.
Pubblicazione: (2025)

Enabling On-Chip High-Frequency Adaptive Linear Optimal Control via Linearized Gaussian Process
di: Gao, Yuan, et al.
Pubblicazione: (2024)

Enforcing Soft Monotonicity Constraints for Recursive Gaussian Process Regression in Real Time
di: Husmann, Ricus, et al.
Pubblicazione: (2026)

Symbolic Regression on Sparse and Noisy Data with Gaussian Processes
di: Hsin, Junette, et al.
Pubblicazione: (2023)

Asynchronous Distributed Gaussian Process Regression for Online Learning and Dynamical Systems: Complementary Document
di: Yang, Zewen, et al.
Pubblicazione: (2024)

Distributed Time-Varying Gaussian Regression via Kalman Filtering
di: Taddei, Nicola, et al.
Pubblicazione: (2025)

Optimal Honeypot Ratio and Convergent Fictitious-Play Learning in Signaling Games for CPS Defense
di: Xu, Yueyue, et al.
Pubblicazione: (2025)

Characterizing Human Feedback-Based Control in Naturalistic Driving Interactions via Gaussian Process Regression with Linear Feedback
di: DiPirro, Rachel, et al.
Pubblicazione: (2025)

A Taylor Series Approach to Correction of Input Errors in Gaussian Process Regression
di: Qureshi, Muzaffar, et al.
Pubblicazione: (2025)

ViSTR-GP: Online Cyberattack Detection via Vision-to-State Tensor Regression and Gaussian Processes in Automated Robotic Operations
di: Aftabi, Navid, et al.
Pubblicazione: (2025)

Data-Driven Nonlinear Regulation: Gaussian Process Learning
di: Harry, Telema, et al.
Pubblicazione: (2025)

Uniform Error Bounds for Gaussian Process Regression with Application to Safe Control
di: Lederer, Armin, et al.
Pubblicazione: (2019)

Time-Optimal Control for High-Order Chain-of-Integrators Systems with Full State Constraints and Arbitrary Terminal States (Extended Version)
di: Wang, Yunan, et al.
Pubblicazione: (2023)

Powered Descent Guidance via First-Order Optimization with Expansive Projection
di: Choi, Jiwoo, et al.
Pubblicazione: (2023)

Decentralized Event-Triggered Online Learning for Safe Consensus of Multi-Agent Systems with Gaussian Process Regression
di: Dai, Xiaobing, et al.
Pubblicazione: (2024)

Carbon-Aware Optimal Power Flow
di: Chen, Xin, et al.
Pubblicazione: (2023)

Robust Near-Optimal Nonlinear Target Enclosing Guidance
di: Sinha, Abhinav, et al.
Pubblicazione: (2025)

Multi-Agent Clarity-Aware Dynamic Coverage with Gaussian Processes
di: Agrawal, Devansh R., et al.
Pubblicazione: (2024)

Safe Exploration for Nonlinear Processes Using Online Gaussian Process Learning
di: Tonini, Stefano, et al.
Pubblicazione: (2026)

Bang-Bang Evasion: Its Stochastic Optimality and a Terminal-Set-Based Implementation
di: Mudrik, Liraz, et al.
Pubblicazione: (2025)