8.6 Robotics and Industry 4.0

Printer-friendly version PDF version

Date: Wednesday, March 27, 2019
Time: 17:00 - 18:30
Location / Room: Room 6

Chair:
Federica Ferraguti, University of Modena-Reggio, IT, Contact Federica Ferraguti

Co-Chair:
Armin Schoenlieb, Infineon Technologies, AT, Contact Armin Schoenlieb

This session presents new results in the field of robotics and cyberphysical systems applied to Industry 4.0. The session includes theoretical results as well as evaluation of relevant use-cases.

TimeLabelPresentation Title
Authors
17:008.6.1A METHODOLOGY FOR COMPARATIVE ANALYSIS OF COLLABORATIVE ROBOTS FOR INDUSTRY 4.0
Speaker:
Marcello Bonfè, University of Ferrara, IT
Authors:
Federica Ferraguti1, Andrea Pertosa1, Cristian Secchi1, Cesare Fantuzzi1 and Marcello Bonfè2
1University of Modena and Reggio Emilia, IT; 2University of Ferrara, IT
Abstract
Collaborative robots are one of the key drivers in Industry 4.0 and they have evolved considerably since the last decades of the 20th century. With respect to the industrial robots, collaborative robots are more productive, flexible, versatile and safer. In the recent years, both market leading manufacturers of industrial robots and newer startup companies have developed novel products for collaborative robotic applications. In this paper, we propose a methodology for developing a comparative analysis of the collaborative robots currently available in the market. The goal of the paper is to provide a framework for benchmarking alternative robots for a given collaborative application, based on common robot parameters and standardized experiments to be performed with the robots under investigation. An experimental technological review of three different collaborative robots is provided, showing how the methodology can be applied in real cases.
17:308.6.2HYBRID SENSING APPROACH FOR CODED MODULATION TIME-OF-FLIGHT CAMERAS
Speaker:
Armin Schoenlieb, Infineon Technologies, AT
Authors:
Armin Schoenlieb1, Hannes Plank1, Christian Steger2, Gerald Holweg3 and Norbert Druml3
1Infineon Technologies Austria, AT; 2Graz University of Technology, AT; 3Infineon Technologies Austria AG, AT
Abstract
In recent years, application fields such as industrial automation and indoor robot navigation increased the demand on reliable localization systems. Simultaneous mapping and localization systems often depend on depth imaging in order to reconstruct the scene. Time-of-Flight sensors prove to be well suited for these applications, however are impaired by different error sources. The measurement principle is based on measuring the phase and consequently the delay of emitted and reflected light. Specular surfaces can cause pixel saturation, while the periodicity of the measured phase leads to ambiguous distances. In this paper, we aim to solve these problems by proposing a new Time-of- Flight depth sensing approach. By combining the emerging coded modulation method with traditional depth sensing, we are able to unify the advantages of both methods. Images captured with coded modulation show a pixel response only within selected distance limits. In contrast traditional continuous wave Time- of-Flight imaging exhibits a superior signal-to-noise ratio. This method enables to mask erroneous distance measurements, al- lowing Time-of-Flight sensors to produce more reliable depth measurements and gain traction in the industrial environment. As our evaluation shows, our method is able to remove the influence of specular surfaces, and is capable of masking ambiguous distance measurements. Furthermore, our approach improves the system behavior by enabling more robust exposure time control.
18:008.6.3COMMUNICATION-COMPUTATION CO-DESIGN OF DECENTRALIZED TASK CHAIN IN CPS APPLICATIONS
Speaker:
Eli Bozorgzadeh, , US
Authors:
Seyyed Ahmad Razavi, Eli Bozorgzadeh and Solmaz Kia, University of California, Irvine, US
Abstract
In this paper, we present a method to find an optimal trade-off between computation and communication of decentralized linear task chain running on a network of mobile agents. Task replication has been deployed to reduce the data links among highly correlated nodes in communication networks. The primary goal is to reduce or remove the data links at the cost of increase in computational load at each node. However, with increase in complexity of applications and computation load on end devices with limited resources, the computational load is not negligible. Our proposed selective task replication enables communication-computation trade-off in decentralized task chains and minimizes the overall local computation overhead while keeping the critical path delay under a threshold delay. We applied our approach to decentralized Unscented Kalman Filter (UKF) for state estimation in cooperative localization of mobile multi-robot systems. We demonstrate and evaluate our proposed method on a network of 15 Raspberry Pi3B connected via WiFi. Our experimental results show that, using the proposed method, the prediction step of decentralized UKF is faster by 15%, and for the same threshold delay, the overall computation overhead is reduced by 2.41 times, compared to task replication without resource constraint.
18:158.6.4RESOURCE MANAGER FOR SCALABLE PERFORMANCE IN ROS DISTRIBUTED ENVIRONMENTS
Speaker:
Daisuke Fukutomi, Ritsumeikan University, JP
Authors:
Daisuke Fukutomi1, Takuya Azumi2, Shinpei Kato3 and Nobuhiko Nishio1
1Ritsumeikan University, JP; 2Saitama University, JP; 3The University of Tokyo, JP
Abstract
This paper presents a resource manager to achieve scalable performance in Robot Operating System (ROS) for distributed environments. In robotics, using ROS in distributed environments via multiple host machines is trending for large-scale data processing, for example, cloud/edge computing and the data communication of point clouds and images in dynamic map composition. However, ROS is unable to manage the resources (e.g., the CPUs, memory, and disks) on each host machine. Therefore, it is difficult to use distributed environmental resources efficiently and achieve scalable performance. This paper proposes a resource management mechanism for ROS distributed environments using a master-slave model to execute ROS processes efficiently and smoothly. We manage the resource usage of each host machine and construct a mechanism to adaptively distribute the load to be balanced. Evaluations show that scalable performance can be achieved in ROS distributed environments comprising ten host machines using a real application (SLAM: simultaneous localization and mapping) processing large-scale point cloud data.
18:31IP4-4, 791FROM MULTI-LEVEL TO ABSTRACT-BASED SIMULATION OF A PRODUCTION LINE
Speaker:
Stefano Centomo, University of Verona, IT
Authors:
Stefano Centomo1, Enrico Fraccaroli2 and Marco Panato1
1University of Verona, IT; 2Università degli Studi di Verona, IT
Abstract
This paper proposes two approaches for the integration of cyber-physical systems in a production line in order to obtain predictions concerning the actual production, core operation in the context of Industry 4.0. The first approach relies on the Multi-Level paradigm where multiple descriptions of the same CPS are modeled with different levels of details. Then, the models are switched at runtime. The second approach relies on abstraction techniques of CPS maintaining a certain levels of details. The two approaches are validated and compared with a real use case scenario to identify the most effective simulation strategy.
18:32IP4-5, 285ACCURATE DYNAMIC MODELLING OF HYDRAULIC SERVOMECHANISMS
Speaker:
Manuel Pencelli, Yanmar R&D Europe S.r.l., IT
Authors:
Manuel Pencelli1, Renzo Villa2, Alfredo Argiolas1, Gianni Ferretti2, Marta Niccolini1, Matteo Ragaglia1, Paolo Rocco2 and Andrea Maria Zanchettin2
1YANMAR R&D EUROPE S.R.L, IT; 2Politecnico di Milano, IT
Abstract
In this paper, the process of modelling and identification of a hydraulic actuator is discussed. In this framework a simple model based on the classical theory have been derived and a first experimental campaign has been performed on a test bench. These tests highlighted the presence of unmodelled phenomena (dead-zone, hysteresis, etc.), therefore a second and more extensive set of experiments has been done. With the acquired knowledge a new improved model is presented and its parameter identified. Finally several test has been performed in order to experimentally validate the model.
18:33IP4-6, 208PLANNING WITH REAL-TIME COLLISION AVOIDANCE FOR COOPERATING AGENTS UNDER RIGID BODY CONSTRAINT
Speaker:
Federico Vesentini, University of Verona, IT
Authors:
Nicola Piccinelli, Federico Vesentini and Riccardo Muradore, University of Verona, IT
Abstract
In automated warehouses, path planning is a crucial topic to improve automation and efficiency. This kind of planning is usually computed off-line knowing the planimetry of the warehouse and the starting and target points of each agent. However, this global approach is not able to manage unexpected static/dynamic obstacles and other agents moving in the same area. For this reason in multi-robot systems global planners are usually integrated with local collision avoidance algorithms. In this paper we use the Voronoi diagram as global planner and the Velocity Obstacle (VO) method as collision avoidance algorithm. The goal of this paper is to extend such hybrid motion planner by enforcing mechanical constraints between agents in order to execute a task that cannot be performed by a single agent. We will focus on the cooperative task of carrying a payload, such as a bar. Two agents are constrained to move at the end points of the bar. We will improve the original algorithms by taking into account dynamically the constrained motion both at the global and at the collision avoidance level.
18:30End of session