Safe learning in robotics: From learning-based control to safe reinforcement learning
The last half decade has seen a steep rise in the number of contributions on safe learning
methods for real-world robotic deployments from both the control and reinforcement learning …
methods for real-world robotic deployments from both the control and reinforcement learning …
Crossing the reality gap: A survey on sim-to-real transferability of robot controllers in reinforcement learning
The growing demand for robots able to act autonomously in complex scenarios has widely
accelerated the introduction of Reinforcement Learning (RL) in robots control applications …
accelerated the introduction of Reinforcement Learning (RL) in robots control applications …
Optimization-based control for dynamic legged robots
In a world designed for legs, quadrupeds, bipeds, and humanoids have the opportunity to
impact emerging robotics applications from logistics, to agriculture, to home assistance. The …
impact emerging robotics applications from logistics, to agriculture, to home assistance. The …
Robot learning from randomized simulations: A review
The rise of deep learning has caused a paradigm shift in robotics research, favoring
methods that require large amounts of data. Unfortunately, it is prohibitively expensive to …
methods that require large amounts of data. Unfortunately, it is prohibitively expensive to …
Reinforcement learning for robot research: A comprehensive review and open issues
T Zhang, H Mo - International Journal of Advanced Robotic …, 2021 - journals.sagepub.com
Applying the learning mechanism of natural living beings to endow intelligent robots with
humanoid perception and decision-making wisdom becomes an important force to promote …
humanoid perception and decision-making wisdom becomes an important force to promote …
Policy search for model predictive control with application to agile drone flight
Y Song, D Scaramuzza - IEEE Transactions on Robotics, 2022 - ieeexplore.ieee.org
Policy search and model predictive control (MPC) are two different paradigms for robot
control: policy search has the strength of automatically learning complex policies using …
control: policy search has the strength of automatically learning complex policies using …
Variable impedance control and learning—a review
FJ Abu-Dakka, M Saveriano - Frontiers in Robotics and AI, 2020 - frontiersin.org
Robots that physically interact with their surroundings, in order to accomplish some tasks or
assist humans in their activities, require to exploit contact forces in a safe and proficient …
assist humans in their activities, require to exploit contact forces in a safe and proficient …
Review of deep reinforcement learning-based object grasping: Techniques, open challenges, and recommendations
MQ Mohammed, KL Chung, CS Chyi - IEEE Access, 2020 - ieeexplore.ieee.org
The motivation behind our work is to review and analyze the most relevant studies on deep
reinforcement learning-based object manipulation. Various studies are examined through a …
reinforcement learning-based object manipulation. Various studies are examined through a …
A review on manipulation skill acquisition through teleoperation‐based learning from demonstration
Manipulation skill learning and generalisation have gained increasing attention due to the
wide applications of robot manipulators and the spurt of robot learning techniques …
wide applications of robot manipulators and the spurt of robot learning techniques …
Skill transfer learning for autonomous robots and human–robot cooperation: A survey
Designing a robot system with reasoning and learning ability has gradually become a
research focus in robotics research field. Recently, Skill Transfer Learning (STL), ie, the …
research focus in robotics research field. Recently, Skill Transfer Learning (STL), ie, the …