A survey on deep reinforcement learning algorithms for robotic manipulation
Robotic manipulation challenges, such as grasping and object manipulation, have been
tackled successfully with the help of deep reinforcement learning systems. We give an …
tackled successfully with the help of deep reinforcement learning systems. We give an …
[HTML][HTML] A review on reinforcement learning for contact-rich robotic manipulation tasks
Í Elguea-Aguinaco, A Serrano-Muñoz… - Robotics and Computer …, 2023 - Elsevier
Research and application of reinforcement learning in robotics for contact-rich manipulation
tasks have exploded in recent years. Its ability to cope with unstructured environments and …
tasks have exploded in recent years. Its ability to cope with unstructured environments and …
Diff-lfd: Contact-aware model-based learning from visual demonstration for robotic manipulation via differentiable physics-based simulation and rendering
Abstract Learning from Demonstration (LfD) is an efficient technique for robots to acquire
new skills through expert observation, significantly mitigating the need for laborious manual …
new skills through expert observation, significantly mitigating the need for laborious manual …
Efficient sim-to-real transfer of contact-rich manipulation skills with online admittance residual learning
Learning contact-rich manipulation skills is essential. Such skills require the robots to
interact with the environment with feasible manipulation trajectories and suitable compliance …
interact with the environment with feasible manipulation trajectories and suitable compliance …
Factory: Fast contact for robotic assembly
Robotic assembly is one of the oldest and most challenging applications of robotics. In other
areas of robotics, such as perception and grasping, simulation has rapidly accelerated …
areas of robotics, such as perception and grasping, simulation has rapidly accelerated …
Industreal: Transferring contact-rich assembly tasks from simulation to reality
Robotic assembly is a longstanding challenge, requiring contact-rich interaction and high
precision and accuracy. Many applications also require adaptivity to diverse parts, poses …
precision and accuracy. Many applications also require adaptivity to diverse parts, poses …
A model-based hybrid soft actor-critic deep reinforcement learning algorithm for optimal ventilator settings
A ventilator is a device that mechanically assists in pumping air into the lungs, which is a life-
saving supportive therapy in an intensive care unit (ICU). In clinical scenarios, each patient …
saving supportive therapy in an intensive care unit (ICU). In clinical scenarios, each patient …
Bridging the sim-to-real gap with dynamic compliance tuning for industrial insertion
Contact-rich manipulation tasks often exhibit a large sim-to-real gap. For instance, industrial
assembly tasks frequently involve tight insertions where the clearance is less than 0.1 mm …
assembly tasks frequently involve tight insertions where the clearance is less than 0.1 mm …
Prim-lafd: A framework to learn and adapt primitive-based skills from demonstrations for insertion tasks
Learning generalizable insertion skills in a data-efficient manner has long been a challenge
in the robot learning community. While the current state-of-the-art methods with …
in the robot learning community. While the current state-of-the-art methods with …
Learning generalizable pivoting skills
The skill of pivoting an object with a robotic system is challenging for the external forces that
act on the system, mainly given by contact interaction. The complexity increases when the …
act on the system, mainly given by contact interaction. The complexity increases when the …