Intelligent Experiment Robotic Systems Design for Material Preparation and Detection

Abstract

This article presents an intelligent robotic system developed for experiments in the materials science laboratory, specifically focusing on coating preparation via layer-by-layer self-assembly techniques and hydrophobic detection. The system integrates two collaborative robotic arms, enhanced with dynamic movement primitives (DMPs), to mimic human manipulation skills and bolster the robots’ imitation capabilities. Additionally, a mobile robotic arm facilitates autonomous operations. A key component is an independently designed optical detection device capable of measuring water droplet angles. Coupled with a compatible simulation platform, the system can perform virtual experiments and generate trajectories for obstacle avoidance, and in which generative adversarial imitation learning (GAIL) in simulating robot trajectories. This article details the system’s construction, process design encompassing the robotic systems, optical detection device, simulation, and visualization platform. It also explores the vast potential of future AI-driven laboratories in materials science, biology, medicine, and chemistry.