This paper proposes an improved residual deep reinforcement learning method for robot arm dynamic obstacle avoidance and position servo. The proposed method first simplifies the state space by ...

To address the issues of extensive calculation and low efficiency in path planning for the robotic arm of a mobile exploration robot operating in complex environments, a local environment construction ...

Upper limb impairment is a common challenge for individuals who have suffered a stroke, particularly affecting distal joint mobility. In recent years, advancements in mobility aids, such as ...

The growing interest in arm robotics is driven by the need to facilitate complex and repetitive jobs for humans, as well as by the advancement of production. There is a need for optimal control ...

High-Dimensional Path Planning with Optimized RRT This repository provides a simulation environment for a robotic arm to plan paths for grasping objects within a scene using Rapidly-exploring Random ...

Continuum robots have gained recognition as a promising treatment modality for endoscopic sinus surgery. In many real-world scenarios, tasks often require the collaborative efforts of multiple ...

In order to improve the picking efficiency of cotton picking robotic arm in cotton field, this study analyses the spatial distribution of cotton plasmodesmata, optimizes the path planning problem of ...

Implementing obstacle avoidance (OA) motion control is part and parcel of redundant robot manipulators. Various OA schemes have been designed at the level of joint velocity or joint acceleration. In ...

Developing deep underground energy resources is crucial for addressing our country's energy imbalance. To tackle unsafe conditions and high communication latency, we designed a Remote Control ...

Robotic arms are key components in fruit-harvesting robots. In agricultural settings, conventional serial or parallel robotic arms often fall short in meeting the demands for a large workspace, rapid ...

Medical applications of robots are increasingly popular to objectivise and speed up the execution of several types of diagnostic and therapeutic interventions. Particularly important is a class of ...

In response to the problems of slow convergence and poor control effect when the traditional Deep Deterministic Policy Gradient (DDPG) algorithm is used to train the vehicle-mounted robotic arm, an ...