Deep reinforcement learning (DRL) has achieved great success across multiple fields; however, in the field of robot control, the acquisition of large amounts of motion data from real robots is challenging. In this work, an algorithm is proposed to train a neural network model with a large amount of data in a simulated environment and then transfer the model to the real … [Read more...] about Mastering the Complex Assembly Task With a Dual-Arm Robot: A Novel Reinforcement Learning Method
Manipulators
A Robust Visual Servoing Controller for Anthropomorphic Manipulators With Field-of-View Constraints and Swivel-Angle Motion
Human–robot collaboration has attracted significant attention in the industry due to the flexibility of humans and the accuracy of robots. Humanoid control of anthropomorphic robotic arms combined with visual servoing will enhance the intelligence of industrial robots. However, the robotic manipulator will introduce psychological discomfort to nearby humans, and the loss of … [Read more...] about A Robust Visual Servoing Controller for Anthropomorphic Manipulators With Field-of-View Constraints and Swivel-Angle Motion
A Cable-Driven Hyperredundant Manipulator: Obstacle-Avoidance Path Planning and Tension Optimization
Manipulators with a hyperredundant and large aspect ratio are becoming more commonly used to detect complex and narrow spaces. The hyperredundant feature confers advantages for such manipulator types in comparison to traditional manipulators. However, they also introduce path-planning challenges. Due to the characteristics of hyperredundancy, there are countless inverse … [Read more...] about A Cable-Driven Hyperredundant Manipulator: Obstacle-Avoidance Path Planning and Tension Optimization
