Search results

The purpose of this paper is to analyse teleoperation of an ABB industrial robot with an ABB IRC5 controller. A method to improve motion smoothness and decrease latency using the existing ABB IRC5 robot controller without access to any low-level interface is proposed.

The proposed control algorithm includes a high-level proportional-integral-derivative controller (PID) controller used to dynamically generate reference velocities for different travel ranges of the tool centre point (TCP) of the robot. Communication with the ABB IRC5 controller was performed utilising the ABB PC software development kit. The multitasking feature of the IRC5 controller was used to enhance the communication frequency between the controller and the remote application. Trajectory tracking experiments of a pre-defined three-dimensional trajectory were carried out and the benefits of the proposed algorithm were demonstrated. The robot was intentionally installed on a wobbly table and its vibrations were recorded using a six-degrees-of-freedom force/torque sensor fitted to the tool mounting interface of the robot. The robot vibrations were used as a measure of the smoothness of the tracking movements.

A communication rate of up to 250 Hz between the computer and the controller was established using C# .Net. Experimental results demonstrating the robot TCP, tracking errors and robot vibrations for different control approaches were provided and analysed. It was demonstrated that the proposed approach results in the smoothest motion with tracking errors of < 0.2 mm.

The proposed approach may be employed to produce smooth motion for a remotely operated ABB industrial robot with the existing ABB IRC5 controller. However, to achieve high-bandwidth path following, the inherent latency of the controller must be overcome, for example by utilising a low-level interface. It is particularly useful for applications including a large number of short manipulation segments, which is typical in teleoperation applications.

Using the proposed technique, off-the-shelf industrial robots can be used for research and industrial applications where remote control is required.

Although low-level control interface for industrial robots seems to be the ideal long-term solution for teleoperation applications, the proposed remote control technique allows out-of-the-box ABB industrial robots with IRC5 controllers to achieve high efficiency and manipulation smoothness without requirements of any low-level programming interface.

The purpose of this paper is to present a control system for a heavy duty industrial robot, including both the control structure and algorithm, which was designed and tested.

An industrial PC with TwinCAT real‐time system is chosen as the motion control unit; EtherCAT is used for command transmission. The whole system has a decoupled and centralized control structure. A novel optimal motion generation algorithm based on modified cubic spline interpolation is illustrated. The execution time and work were chosen as the objective function. The constraints are the limits of torque, velocity and jerk. The motion commands were smooth enough throughout the execution period. By using the Lagangue equation and assumed modes methods, a dynamic model of heavy duty industrial robots is built considering the elastic of both joints and links. After that a compound control algorithm based on singular perturbation theory was designed for the servo control loop.

The final experimental results showed that the control commands and algorithms could easily be calculated and transmitted in one sample unit. Both the motion generation and servo control algorithm greatly improved the control performance of the robot.

All parts of the control algorithm can be computed on‐line except the optimal motion generation part. The motion generation part is time consuming (about 2.5 seconds), which can only be performed off‐line. Hence future work will focus on improving the efficiency of this algorithm; therefore it could be performed online, increasing the robot's overall robustness and adaptability.

Aiming at the internal and external causes that limit the dynamic performance of heavy duty industrial robots, this paper proposes a realizable scheme of control system and includes both the control structure and algorithms. A novel optimal motion generation algorithm is presented.

Different machines are already present in the human environment, easing human beings' daily life. In the future, this tendency will be accentuated by integration of numerous robots (e.g. wheeled robots, legged robots, humanoid robots, network sensors, etc.) in the human environment. A wide range of applications, such as those dealing with warehouse management, industrial assembling, military applications, daily‐life tasks, can benefit from multi‐robot systems. The purpose of this paper is to propose an intelligent system for industrial robotics in the logistic field, based on collaboration between heterogeneous robots.

The proposed infrastructure for this multi‐robot system is composed of a robots' network including one humanoid robot, wheeled robots, cameras, and remote computer. All devices can communicate between them by using wireless network. The goal of the humanoid robot is to lead the wheeled robots according to the environment and wheeled robots are used to carry a load. The camera allows providing complementary information about the environment; and thanks to machine learning, this control strategy allows complex tasks to be perormed for these logistic applications.

This concept is implemented on real robots within the frame of a demonstrator including the above‐mentioned kind of robots. The preliminary results, obtained during experimentations, prove the feasibility of the presented strategy for real applications.

The main originalities of this work are, on the one hand, the use of an heterogeneous multi‐robots system for logistic tasks, and on the other hand, the proposed machine learning allows a collaboration task between heterogeneous robots in an autonomous manner.

Most industrial robots are still programmed using the typical teaching process, through the use of the robot teach pendant. This is a tedious and time‐consuming task that requires some technical expertise, and hence new approaches to robot programming are required. The purpose of this paper is to present a robotic system that allows users to instruct and program a robot with a high‐level of abstraction from the robot language.

The paper presents in detail a robotic system that allows users, especially non‐expert programmers, to instruct and program a robot just showing it what it should do, in an intuitive way. This is done using the two most natural human interfaces (gestures and speech), a force control system and several code generation techniques. Special attention will be given to the recognition of gestures, where the data extracted from a motion sensor (three‐axis accelerometer) embedded in the Wii remote controller was used to capture human hand behaviours. Gestures (dynamic hand positions) as well as manual postures (static hand positions) are recognized using a statistical approach and artificial neural networks.

It is shown that the robotic system presented is suitable to enable users without programming expertise to rapidly create robot programs. The experimental tests showed that the developed system can be customized for different users and robotic platforms.

The proposed system is tested on two different robotic platforms. Since the options adopted are mainly based on standards, it can be implemented with other robot controllers without significant changes. Future work will focus on improving the recognition rate of gestures and continuous gesture recognition.

The key contribution of this paper is that it offers a practical method to program robots by means of gestures and speech, improving work efficiency and saving time.

This paper presents an alternative to the typical robot teaching process, extending the concept of human‐robot interaction and co‐worker scenario. Since most companies do not have engineering resources to make changes or add new functionalities to their robotic manufacturing systems, this system constitutes a major advantage for small‐ to medium‐sized enterprises.

At present, the majority of industrial robots are not well suited to the specific needs of the food industry. Additionally, the high cost of robotic systems means that it is currently difficult for food manufacturers to financially justify the use of this technology. This paper aims to examine the unique requirements of the food industry with regards to robot manipulator design and outlines the design features of a low‐cost robotic arm developed specifically for use in food production.

Considerations for the design of the robot arm in addition to industrial requirements for hygienic design, low cost, fast pick and place speed, safety for operation alongside human workers and ease of reprogramming are discussed in detail.

A successful manipulator design must consider functional requirements relevant to food production from the very outset of the design process. The principal three requirements are those of ease of cleaning, speed and low cost.

The availability of low‐cost industrial robots specifically designed for food production might encourage a wider adoption of robotics and automation in the food industry and would benefit food manufacturers by reducing production costs and increasing competitiveness in what is becoming an increasingly difficult market.

This paper is of value to engineers and researchers developing robotic manipulators for use in the food industry.

In this paper, a small revision on force control strategies is presented, stressing the implementation requirements of each strategy with the objective of clarifying the reasons of their poor practical utilization in industry. Furthermore, recognizing that direct force control approaches require system changes on actual robot control systems, which calls for manufacturer cooperation, an indirect force control approach is presented. The controller is introduced along with implementation description. The system is tested with an industrial deburring application that is also briefly introduced. Research experimental results of the proposed controller obtained in the laboratory, and experimental results obtained with the industrial deburring application are presented and discussed.

Force/torque sensing is very important for several automatic and industrial robotic applications. Basically, if precise control of the forces that arise from contact between tools and parts is required to successfully complete the automatic task, then a force/torque sensor is needed along with some force/torque control technique. In this paper we focus on force/torque sensing aspects applied to industrial robotic tasks. Concentrating on a particular type of force/torque sensor, we demonstrate how to use them and how to integrate them into force/torque control applications using robots. Finally, an industrial application is presented where force control was fundamental for the success of the task.

The purpose of this paper is to present work which is a part of the Comprehensive Automation for Specialty Crops project (CASC). Desired trajectory tracking objective has been previously performed by using a non‐model based approach in this project. Long distance autonomous drive has been achieved; however the results haven't met the expectations of the project requirements. In order to provide these requirements, this study is conducted. In this study, long distance autonomous trajectory tracking for an orchard vehicle is studied. Besides longitudinal motion, lateral motion of the vehicle is also considered. The longitudinal and lateral errors are objected to keep into a region of less than 10 cm.

Car‐like robot kinematic modeling approach is used to create desired trajectory. In order to control longitudinal velocity and steering angle of the vehicle, a controller methodology is proposed. Stability of the controller proposed is shown by using Lyapunov stability approach.

The proposed model is adapted into a four‐wheeled autonomous orchard vehicle and tested in an experimental orchard for long distance autonomous drives. More than 15 km autonomous drive is successfully achieved and the details are presented in this paper.

In this study, long distance autonomous trajectory tracking for an orchard vehicle is focused. A model based control strategy, including the information about longitudinal and lateral motion of the vehicle, is constructed. A new approach to create steering angles for turning operations of the orchard vehicle is introduced. It is objected that the longitudinal and lateral errors should be less than 10 cm during the trajectory tracking task.