A novel model-based robust control design for collaborative robot joint module

In order to reduce the impact of load and system parameter changes on the dynamic performance of collaborative robot joint module, a novel robust control algorithm is proposed in this paper to solve the problem of dynamic control of collaborative robot joint module trajectory tracking. The controller is composed of two parts: one is a nominal control term designed based on the dynamical model, aiming to stabilize the nominal robot system; the other is a robust control term based on the Lyapunov method, aiming to eliminate the influence of uncertainty on tracking performance, where the uncertainties include nonlinear friction, parameter uncertainty, and external disturbances. The Lyapunov minimax method is adopted to prove that the system is uniformly bounded and uniformly ultimately bounded. We performed numerical simulation and experimental validation based on an actual collaborative robot joint module experimental platform and the rapid controller prototype cSPACE. The numerical simulation and experimental results show that the controller has excellent control performance for the collaborative robot joint module and provides more accurate trajectory tracking under the influence of uncertainties.

Lab Scale Model Experiment of Smart Hopper System to Remove Blockages Using Machine Vision and Collaborative Robot

In this study, we propose a smart hopper system that automatically unblocks obstructions caused by rocks dropped into hoppers at mining sites. The proposed system captures RGB (red green blue) and D (depth) images of the upper surfaces of hopper models using an RGB-D camera and transmits them to a computer. Then, a virtual hopper system is used to identify rocks via machine vision-based image processing techniques, and an appropriate motion is simulated in a robot arm. Based on the simulation, the robot arm moves to the location of the rock in the real world and removes it from the actual hopper. The recognition accuracy of the proposed model is evaluated in terms of the quantity and location of rocks. The results confirm that rocks are accurately recognized at all positions in the hopper by the proposed system.

Analysing Factory Workers’ Acceptance of Collaborative Robots: A Web-Based Tool for Company Representatives

Collaborative robots are a new type of lightweight robots that are especially suitable for small and medium-sized enterprises. They offer new interaction opportunities and thereby pose new challenges with regard to technology acceptance. Despite acknowledging the importance of acceptance issues, small and medium-sized enterprises often lack coherent strategies to identify barriers and foster acceptance. Therefore, in this article, we present a collection of crucial acceptance factors with regard to collaborative robot use at the industrial workplace. Based on these factors, we present a web-based tool to estimate employee acceptance, to provide company representatives with practical recommendations and to stimulate reflection on acceptance issues. An evaluation with three German small and medium-sized enterprises reveals that the tool’s concept meets the demands of small and medium-sized enterprises and is perceived as beneficial as it raises awareness and deepens knowledge on this topic. In order to realise economic potentials, further low-threshold usable tools are needed to transfer research findings into the daily practice of small and medium-sized enterprises.

A compliance modeling method of flexible rotary joint for collaborative robot using passive network synthesis theory

Collaborative robots have become a research focus because of their wide applications. However, the previous compliance design method of the flexible rotary joint for collaborative robot mainly relied on experience of designers, and “trial and error” method is usually adopted, no feasible and systematic theory for the designer to select numerical value and series-parallel connection mode of the springs and dampers for the flexible rotary joint. Thus, developing a feasible compliance modeling theory to guide the design of the flexible rotary joint is a particularly challenging task. The main contribution of this paper is to present a novel and effective compliance modeling theory of the flexible rotary joint for collaborative robot based on electrical and mechanical passive network synthesis, to provide theoretical and systematic guidances for compliance design of the flexible rotary joint. First, inerter element is introduced into the mechanical system, and the compliance of the flexible rotary joint is expressed as an angular velocity admittance function using electrical and mechanical network analogy. Then, by passive network synthesis theory, the three kinds of compliance realization forms of rational function and four-element compliance realization conditions of biquadratic function for the flexible rotary joint are given using inerters, springs, and dampers. Moreover, numerical examples and simulations are conducted to illustrate effectiveness of the proposed compliance realization method. Finally, discussions are given to illustrate advantages of the proposed compliance modeling and design methods compared with the previous method.

IMPROVING HUMAN AWARENESS DURING COLLABORATION WITH ROBOT: REVIEW

Human-robot collaboration is a widespread topic within the concept of Industry 4.0. Such collaboration brings new opportunities to improve ergonomics and innovative options for manufacturing automation; however, most of the modern collaborative industrial applications are limited by the fact that neither collaborative side is fully aware of the partner: the human operator may not see the robot movement due to own engagement in the work process, and the collaborative robot simply has no means of knowing the position of the operator. Dynamic replanning of the robot trajectory with respect to the operator's current position can increase the efficiency and safety of cooperation since the robot will be able to avoid collisions and proceed in task completion; however, the other side of communication remains unresolved. This paper provides a review of methods of improving human awareness during collaboration with a robot. Covered techniques include graphical, acoustic and haptic feedback implementations. The work is focused on the practical applicability of the approaches, and analyses present challenges associated with each method.

ANALYSIS OF INCREASING THE FRICTION FORCE OF THE ROBOT JAWS BY ADDING 3D PRINTED FLEXIBLE INSERTS

3D printing technology plays a key role in the production of prototypes and final functional parts. The ability to produce almost any shape using this technology in combination with lightweight materials is often used to minimise the weight of the designed components. However, for some applications, such as robot gripper jaws, conventional most commonly used materials, such as PLA, may be unsuitable due to their low coefficient of friction on the material of the manipulated object, which in some cases may cause the object to slip in the robot jaws. This article describes a technical problem from practice, where a manipulated object made of steel material slipped in the printed PLA jaws of the robot during its working cycle. This work is devoted to increasing the friction force of the robot jaws by adding 3D printed soft inserts. Two insert surface shapes made of two flexible materials TPU 30D and TPE 88 are tested. The increase in friction force is measured on a measuring device with an industrial robot and a force measuring sensor. The most suitable type of inserts and material is then tested on a collaborative robot at its required working cycle. The results of this experiment are intended to help designers as a source of information or inspiration in designing similar applications.

A Human-Following Motion Planning and Control Scheme for Collaborative Robots Based on Human Motion Prediction

Human–Robot Interaction (HRI) for collaborative robots has become an active research topic recently. Collaborative robots assist human workers in their tasks and improve their efficiency. However, the worker should also feel safe and comfortable while interacting with the robot. In this paper, we propose a human-following motion planning and control scheme for a collaborative robot which supplies the necessary parts and tools to a worker in an assembly process in a factory. In our proposed scheme, a 3-D sensing system is employed to measure the skeletal data of the worker. At each sampling time of the sensing system, an optimal delivery position is estimated using the real-time worker data. At the same time, the future positions of the worker are predicted as probabilistic distributions. A Model Predictive Control (MPC)-based trajectory planner is used to calculate a robot trajectory that supplies the required parts and tools to the worker and follows the predicted future positions of the worker. We have installed our proposed scheme in a collaborative robot system with a 2-DOF planar manipulator. Experimental results show that the proposed scheme enables the robot to provide anytime assistance to a worker who is moving around in the workspace while ensuring the safety and comfort of the worker.