Deep learning approaches to grasp synthesis: A review
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 …
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 …
multiple human-controlled demonstrations. However, existing approaches often struggle to …
A gripper-like exoskeleton design for robot grasping demonstration
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 …
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 …
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
While deep reinforcement learning is increasingly used to solve complex sensorimotor
tasks, it requires vast amounts of experience to achieve adequate performance. Humans, by …
tasks, it requires vast amounts of experience to achieve adequate performance. Humans, by …