Deep learning approaches to grasp synthesis: A review

R Newbury, M Gu, L Chumbley… - IEEE Transactions …, 2023 - ieeexplore.ieee.org
Grasping is the process of picking up an object by applying forces and torques at a set of
contacts. Recent advances in deep learning methods have allowed rapid progress in robotic …

Improved generalization of probabilistic movement primitives for manipulation trajectories

X Yao, Y Chen, B Tripp - IEEE Robotics and Automation Letters, 2023 - ieeexplore.ieee.org
Imitation learning methods have proven effective in learning robotic tasks by leveraging
multiple human-controlled demonstrations. However, existing approaches often struggle to …

A gripper-like exoskeleton design for robot grasping demonstration

H Dai, Z Lu, M He, C Yang - Actuators, 2023 - mdpi.com
Learning from demonstration (LfD) is a practical method for transferring skill knowledge from
a human demonstrator to a robot. Several studies have shown the effectiveness of LfD in …

Six-degree-of-freedom manipulator wireless control system based on Internet of Things

Y Zhu, Z Wu, C Liu - Journal of Ambient Intelligence and Humanized …, 2023 - Springer
The robotic arm is an automatic control device that imitates the function of a human arm and
accurately recognizes specific points in the three-dimensional space according to received …

Inferring symbols from demonstrations to support vector-symbolic planning in a robotic assembly task

X Yao, S Nair, P Blouw, B Tripp - ICDL 2020-1st SMILES …, 2020 - inria.hal.science
While deep reinforcement learning is increasingly used to solve complex sensorimotor
tasks, it requires vast amounts of experience to achieve adequate performance. Humans, by …