PATH DRIVEN DUAL ARM MOBILE CO-MANIPULATION ARCHITECTURE FOR LARGE PART MANIPULATION IN INDUSTRIAL ENVIRONMENTS
Aitor Ibarguren, Paul Daelman
October 2021
Collaborative part transportation is an interesting application as many industrial sectors require moving large parts among different areas of the workshops, using a large amount of the workforce on these tasks. Even so, the implementation of such kinds of robotic solutions raises technical challenges like force-based control or robot-to-human feedback. This paper presents a path-driven mobile co-manipulation architecture, proposing an algorithm that deals with all the steps of collaborative part transportation. Starting from the generation of force-based twist commands, continuing with the path management for the definition of safe and collaborative areas, and finishing with the feedback provided to the system users, the proposed approach allows creating collaborative lanes for the conveyance of large components. The implemented solution and performed tests show the suitability of the proposed architecture, allowing the creation of a functional robotic system able to assist operators transporting large parts on workshops.
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A REAL APPLICATION OF AN AUTONOMOUS INDUSTRIAL MOBILE MANIPULATOR IN INDUSTRIAL CONTEXT
Jose Luis Outón, Ibon Merino, Iván Villaverde, Aitor Ibarguren, Héctor Herrero, Paul Daelman, Basilio Sierra
2021
In modern industry, there are still a large number of low added-value processes that can be automated or semi-automated with safe cooperation between robots and human operators. The European SHERLOCK project aims to integrate an autonomous industrial mobile manipulator (AIMM) to perform cooperative tasks between a robot and a human. To be able to do this, AIMMs need to have a variety of advanced cognitive skills like autonomous navigation, smart perception and task management. In this paper, we report the project’s tackle in a paradigmatic industrial application combining accurate autonomous navigation with deep learning-based 3D perception for pose estimation to locate and manipulate different industrial objects in an unstructured environment. The proposed method presents a combination of different technologies fused in an AIMM that achieve the proposed objective with a success rate of 83.33% in tests carried out in a real environment.
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OPERATOR – MOBILE ROBOT COLLABORATION FOR SYNCHRONIZED PART MOVEMENT
Aswin K Ramasubramanian, Nikolaos Papakostas
2021
Mobile robotic platforms have become increasingly popular. Commercially available versions of mobile robots are designed to support human operators in typical production environments. They may be used for transferring parts from one place to another, as well as for assisting the operator in a series of tasks, by utilizing the dexterity of their arm and end effector. This paper focuses on the development of a novel approach that allows the handling and transportation of parts through the simultaneous operation of human operators and mobile robots. In particular, a straightforward, easy to implement control strategy is used to adapt the operation of the mobile robot to the tasks carried out by the operator. This paper discusses also the advantages of introducing mobile robots in typical industrial environments and compares their potential against fully automated robotic solutions.
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ON USING HUMAN ACTIVITY RECOGNITION SENSORS TO IMPROVE THE PERFORMANCE OF COLLABORATIVE MOBILE MANIPULATORS; REVIEW AND OUTLOOK
Aswin K Ramasubramanian, Syed M. Aiman, Nikolaos Papakostas
2021
The operation of mobile manipulators in a collaborative environment needs to be adapted to the characteristics and skills of human operators. Human activity recognition, utilizing wearable sensors and vision systems, could be used to fine-tune the performance of the mobile manipulator so that human operators be better assisted. The goal is to develop a sense of safety and trust between the human and the manipulator in order to improve the ergonomics of the operator within the collaborative workspace. This paper reviews the technologies that can be used for activity tracking together with gait recognition as a biometric tool. These technologies could potentially allow the mobile robotic manipulator to dynamically adapt to the motion, skills, and intentions of the human operator and to the requirements of the task in action. This paper also proposes the idea of combining a gait recognition model and activity tracking towards improving the performance of mobile collaborative robots.
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DUAL ARM CO-MANIPULATION ARCHITECTURE WITH ENHANCED HUMAN-ROBOT COMMUNICATION FOR LARGE PART MANIPULATION
Aitor Ibarguren, Iveta Eimontaite, José Luis Outón, Sarah Fletcher
October 2020
The emergence of collaborative robotics has had a great impact on the development of robotic solutions for cooperative tasks nowadays carried out by humans, especially in industrial environments where robots can act as assistants to operators. Even so, the coordinated manipulation of large parts between robots and humans gives rise to many technical challenges, ranging from the coordination of both robotic arms to the human-robot information exchange. This paper presents a novel architecture for the execution of trajectory driven collaborative tasks, combining impedance control and trajectory coordination in the control loop, as well as adding mechanisms to provide effective robot-to-human feedback for successful and satisfactory task completion. The obtained results demonstrate the validity of the proposed architecture as well as its suitability for the implementation of collaborative robotic systems.
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CONTROL STRATEGIES FOR DUAL ARM CO-MANIPULATION OF FLEXIBLE OBJECTS IN INDUSTRIAL ENVIRONMENTS
Aitor Ibarguren, Paul Daelman, Miguel Prada
June 2020
The introduction of collaborative robots had a great impact in the development of robotic solutions for cooperative tasks typically performed by humans, especially in industrial environments where robots can act as assistants of operators. Even so, the coordinated manipulation of large and deformable parts between dual-arm robots and humans rises many technical challenges, ranging from the coordination of both robotic arms to the detection of the forces applied by the operator. This paper presents a novel control architecture for the execution of trajectory driven collaborative tasks, combining impedance control and trajectory coordination in the control loop. The obtained results demonstrate the validity of the implemented control architecture as well as its suitability for the implementation of collaborative cyber-physical systems.
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ONLINE PREDICTION FOR SAFE HUMAN-ROBOT COLLABORATION: A MODEL OF THE HUMAN ARM
Binchi Jacopo, Mangeruca Leonardo, Rucco Matteo, Orlando Ferrante, Minissale Alfio, Abba Fabio Francesco
2020
With the advent of new technologies and the transition of production to industry 4.0, a more flexible approach to manufacturing is pursued to achieve higher productivity. This transformation leads to overcoming traditional safety procedures and the development of new safety-assuring technologies for the minimization of risks connected with human-robot collaboration. In this work, we focus on the prediction of movements of operators’ upper torso and arms by developing a method which combines data-driven methodologies with formal methods. The approach is based on a predictive model of human motion compared against the planned robot trajectory and online monitoring of satisfaction of safety requirements with formal methods.
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PRELIMINARY DEVELOPMENT OF THE PSYCHOLOGICAL FACTORS ASSESSMENT FRAMEWORK
Eimontaite Iveta, Fletcher Sarah
17 April 2020
Robots, although not new in manufacturing, are still only just being directly integrated with human operators. Although timely and measured human factors integration in technology development can increase its acceptance, the impacts on manufacturing operators are still largely unknown. The proposed work described in this paper discusses the SHERLOCK project approach to human factors integration that aims to develop a standardised tool for evaluating the impacts of robotics in manufacturing. This analysis will enable the development of the framework, which will allow quicker assessment of psychological factors and recommendations for operator needs and requirements in a variety of manufacturing applications.
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AN APPROACH FOR MONITORING THE EXECUTION OF HUMAN-BASED ASSEMBLY OPERATIONS USING MACHINE LEARNING
George Andrianakos, Nikos Dimitropoulos, George Michalos, Sotirios Makris
18 February 2020
Sensing systems have been introduced safeguarding the operators, while primitive workflow monitoring systems, primarily based on operator’s feedback, enhance the dynamic behaviour of the system. This paper presents an approach to automatically monitor the execution of human-based assembly operations using vision sensors and machine learning techniques. A reference example based on the assembly of a water pump is showcasing the effectiveness of the proposed approach in real-life application.
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2D FEATURES-BASED DETECTOR AND DESCRIPTOR SELECTION SYSTEM FOR HIERARCHICAL RECOGNITION OF INDUSTRIAL PARTS
Ibon Merino, Jon Azpiazu, Anthony Remazeilles, Basilio Sierra
5 December 2019
Detection and description of key points from an image is a well-studied problem in Computer Vision. Some methods like SIFT, SURF or ORB are computationally really efficient. This paper proposes a solution for a particular case study on object recognition of industrial parts based on hierarchical classification. Reducing the number of instances leads to better performance, indeed, that is what the use of the hierarchical classification is looking for.
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BOUNDED COLLISION FORCE BY THE SOBOLEV NORM
Kevin Haninger, Dragoljub Surdilovic
12 August 2019
A robot making contact with an environment or human presents potential safety risks, including excessive collision force. Here, the Sobolev norm is adapted to be a system norm, giving rigorous bounds on the maximum force on a stiffness element in a general dynamic system, allowing the study of collision with more accurate models and feedback control.
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WHAT DYNAMICS SHOULD IMPEDANCE-CONTROLLED ROBOTS RENDER?
Kevin Haninger, Dragoljub Surdilovic, Arturo Bastidas Cruz
24 May 2019
While impedance control is the standard framework for physically interactive robots, the design choice of what dynamics should be rendered requires additional information (assumptions on environment, in-situ data). The range of dynamics which can be rendered by a robot is informed by its mechatronic design (actuators, physical compliance, inner loop control), and these mechanical design decisions must be made in advance. How can a mechatronic design be evaluated when the system objectives and environment dynamics are not quantified?
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