SafeAPT: Safe Simulation-to-Real Robot Learning using Diverse Policies
Learned in Simulation

SafeAPT: Safe Simulation-to-Real Robot Learning using Diverse Policies Learned in Simulation

27 January 2022

Rituraj Kaushik

Ville Kyrki

Papers citing "SafeAPT: Safe Simulation-to-Real Robot Learning using Diverse Policies Learned in Simulation"

8 / 8 papers shown

Title
CURE: Simulation-Augmented Auto-Tuning in Robotics Md. Abir Hossen Sonam Kharade Jason M. O'Kane B. Schmerl David Garlan Pooyan Jamshidi 27 1 0 08 Feb 2024
Machine Learning Meets Advanced Robotic Manipulation Saeid Nahavandi R. Alizadehsani D. Nahavandi Chee Peng Lim Kevin Kelly Fernando Bello 24 17 0 22 Sep 2023
Sim-and-Real Reinforcement Learning for Manipulation: A Consensus-based Approach Wenxing Liu Hanlin Niu Wei Pan G. Herrmann J. Carrasco 36 7 0 26 Feb 2023
A Human-Centered Safe Robot Reinforcement Learning Framework with Interactive Behaviors Shangding Gu Alap Kshirsagar Yali Du Guang Chen Jan Peters Alois C. Knoll 34 14 0 25 Feb 2023
Open-Ended Diverse Solution Discovery with Regulated Behavior Patterns for Cross-Domain Adaptation Kang Xu Yan Ma Bingsheng Wei Wei Li 27 3 0 24 Sep 2022
Quality-Diversity Optimization: a novel branch of stochastic optimization Konstantinos Chatzilygeroudis Antoine Cully Vassilis Vassiliades Jean-Baptiste Mouret 65 91 0 08 Dec 2020
Meta Reinforcement Learning for Sim-to-real Domain Adaptation Karol Arndt Murtaza Hazara Ali Ghadirzadeh Ville Kyrki 108 104 0 16 Sep 2019
Emergence of Locomotion Behaviours in Rich Environments N. Heess TB Dhruva S. Sriram Jay Lemmon J. Merel ... Tom Erez Ziyun Wang S. M. Ali Eslami Martin Riedmiller David Silver 134 928 0 07 Jul 2017