ResearchTrend.AI
  • Papers
  • Communities
  • Events
  • Blog
  • Pricing
Papers
Communities
Social Events
Terms and Conditions
Pricing
Parameter LabParameter LabTwitterGitHubLinkedInBlueskyYoutube

© 2025 ResearchTrend.AI, All rights reserved.

  1. Home
  2. Papers
  3. 2304.00790
  4. Cited By
LQR-CBF-RRT*: Safe and Optimal Motion Planning

LQR-CBF-RRT*: Safe and Optimal Motion Planning

3 April 2023
Guangtao Yang
Mingyu Cai
A. Ahmad
Amanda Prorok
Roberto Tron
C. Belta
ArXivPDFHTML

Papers citing "LQR-CBF-RRT*: Safe and Optimal Motion Planning"

4 / 4 papers shown
Title
Safe Navigation in Dynamic Environments Using Data-Driven Koopman Operators and Conformal Prediction
Safe Navigation in Dynamic Environments Using Data-Driven Koopman Operators and Conformal Prediction
Kaier Liang
Guang Yang
Mingyu Cai
C. Vasile
47
0
0
01 Apr 2025
Safe and Dynamically-Feasible Motion Planning using Control Lyapunov and Barrier Functions
Safe and Dynamically-Feasible Motion Planning using Control Lyapunov and Barrier Functions
Pol Mestres
Carlos Nieto-Granda
Jorge Cortés
41
1
0
10 Oct 2024
Visibility-Aware RRT* for Safety-Critical Navigation of Perception-Limited Robots in Unknown Environments
Visibility-Aware RRT* for Safety-Critical Navigation of Perception-Limited Robots in Unknown Environments
Taekyung Kim
Dimitra Panagou
38
3
0
11 Jun 2024
Learning Model Predictive Controllers with Real-Time Attention for
  Real-World Navigation
Learning Model Predictive Controllers with Real-Time Attention for Real-World Navigation
Xuesu Xiao
Tingnan Zhang
K. Choromanski
Edward J. Lee
Anthony G. Francis
...
Leila Takayama
Roy Frostig
Jie Tan
Carolina Parada
Vikas Sindhwani
75
54
0
22 Sep 2022
1