Collaborative robots cooperate with humans to assist them in undertaking simple-to-complex tasks in several fields, including industry, education, agriculture, healthcare services, security, and space exploration. These robots play a vital role in the revolution of Industry 4.0, which defines new standards of manufacturing and the organization of products in the industry. Incorporating collaborative robots in the workspace improves efficiency, but it also introduces several safety risks. Effective safety measures then become indispensable to ensure safe and robust interaction. This paper presents the review of low-level control methodologies of a collaborative robot to assess the current status of human–robot collaboration over the last decade. First, we discuss the classification of human–robot collaboration, architectures of systems and the complex requirements on control strategies. The most commonly used control approaches were presented and discussed. Several methods of control, reported in industrial applications, are elaborated upon with a prime focus on HR-collaborative assembly operations. Since the physical HRC is a critical control problem for the co-manipulation task, this article identifies key control challenges such as the prediction of human intentions, safety, and human-caused disturbances in motion synchronization; the proposed solutions were analyzed afterwards. The discussion at the end of the paper summarizes the features of the control systems that should be incorporated within the systematic framework to allow the execution of a robotic task from global task planning to low-level control implementation for safe and robust interactions.

Snake robots are the multibody mechanisms allowing us to solve specific problems efficiently, i.e., navigate into diverse environments and maneuver through tight spaces or uneven grounds in a way that resembles living organisms. However, the path following and controlling such systems is challenging due to nonlinear dynamics, coupling between links, and nonstandard definitions of the set-point that differ from industrial applications. This paper describes a framework for simulation and evaluation of the controller design for snake robot as the set of tools for the 3D design and robot dynamic simulation. Combined with a theoretical background (equations of robot dynamics), it allows testing new solutions and strategies of robot control design. Firstly, based on the proposed methodology, we provide a mechanical design of a ten-link snake robot. We present control algorithms enabling point-to-point tracking of the robot position in two cases: (i) tracking the center of gravity of the robot and (ii) tracking the position of the head of the robot. Then we provide a simulation-based robustness analysis of a simple fault-tolerant control algorithm, where some snake robot joints are broken. The proposed framework can be used efficiently to study control strategies for multibody mechanisms.

In this article, we present a novel approach to performing engineering simulation in an interactive environment. A synesthetic design approach is employed, which enables the user to gather information about the system’s behaviour more holistically, at the same time as facilitating interaction with the simulated system. The system considered in this work is a snake robot moving on a flat surface. The dynamic simulation of the robot’s movement is realised in dedicated engineering software, whereas this software exchanges information with the 3D visualisation software and a Virtual Reality (VR) headset. Several simulation scenarios have been presented, comparing the proposed method with standard ways for visualising the robot’s motion, such as 2D plots and 3D animations on a computer screen. This illustrates how, in the engineering context, this more immersive experience, allowing the viewer to observe the simulation results and modify the simulation parameters within the VR environment, can facilitate the analysis and design of systems.

This study focuses on enhancing control strategies and locomotion capabilities for underactuated snake robots. A 10-segment underactuated snake robot with 9 Degrees of Freedom (DOF) is modelled and controlled using Model Predictive Control (MPC). MATLAB is utilized to implement the snake robot model and various control algorithms. The simulation results are then integrated into a Virtual Reality (VR) application to visualize the motion of the snake robot. The VR scene generates an animated representation of the snake robot's segments, along with selected physical parameters such as segment velocities, heading angle, and "ghost robots" - predicted positions of the snake robot, along the prediction horizon, calculated by the MPC algorithm. The results demonstrate improved performance and agility of the snake robot by implementing advanced control strategies. The examined strategies enable the robot to navigate in challenging environments even with joint malfunctions.