Conference Agenda

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Session Overview
SES 7.3: Robotics and Computer Integrated Manufacturing
Wednesday, 28/Jun/2017:
4:30pm - 5:50pm

Session Chair: Michele Gadaleta
Location: Aula O (first floor)

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375. PRM Based Motion Planning for Sequencing of Remote Laser Processing Tasks

Sigurd Lazic VIllumsen, Morten Kristiansen

Aalborg Universitet, Denmark

The mechanical system used for remote laser processing can contain as much as 9 degrees of freedom (DOF). In this paper, a sample based motion planning algorithm for such remote laser processing equipment is presented. By construction robot configurations through a sampling strategy redundancy is inherently taken into account and the path is ensured to comply with laser processing constraints. A test showed that the algorithm was capable of finding 1277/1280 possible paths in 2000 iterations for a 9 DOF mechanical system. These 1277 paths were represented in matrix form which can be used for sequencing of laser processing tasks.

220. Automatic Path Planning of Industrial Robots Comparing Sampling-Based and Computational Intelligence Methods

Lars Larsen1, Jonghwa Kim2, Michael Kupke1, Alfons Schuster1

1German Aerospace Center, Germany; 2University of Science & Technology (UST),217 Gajeong-ro, 34113 Daejon, Korea

In times of industry 4.0 a production facility should be “smart”. One result of that property could be that it is easier to reconfigure plants for different products which is, in times of a high rate of variant diversity, a very important point. Nowadays in typical robot based plants, a huge part of time from the commissioning process is needed for the programming of collision free paths. This mainly includes the teach-in or offline programming (OLP) and the optimization of the paths. To speed up this process significantly, an automatic and intelligent planning system is necessary. In this work we present a system which can plan paths industrial robots. We compare widely used sampling-based methods like PRM or RRT with Computational Intelligence (CI) based methods like genetic algorithms.

260. Theoretical and Kinematic Solution of High Reconfigurable Grasping for Industrial Manufacturing

Carlo Canali, Nahian Rahman, Fei Chen, Mariapaola D’imperio, Darwin Caldwell, Ferdinando Cannella

Istituto Italiano di Tecnologia, Italy

High flexibility and high speed is the goal for industrial manufacturing. However, it is difficult to put them together due to the reason that they are contradicting with each other. The authors face this production process problem and presented a new high reconfigurable gripper. It has two degrees of freedom per finger and can support enough payload for manufacturing applications. At same time the simple kinematics permits to be fast. Moreover, not only it is able to handle different workpiece, but the same design concept, can be applied to different scenario. In this paper the authors motivate and detail all the principals and the concepts used for define and design this gripper. The physical models are shown as proof of this successful project.

386. A Simulation Tool for Computing Energy Optimal Motion Parameters of Industrial Robots

Michele Gadaleta2, Giovanni Berselli1, Marcello Pellicciari2, Mario Sposato2

1University of Genova, Italy; 2Enzo Ferrari” Department of Engineering, University of Modena and Reggio Emilia, Via P. Vivarelli, 10, 41125 Modena, Italy

This paper presents a novel robot simulation tool, fully interfaced with a common Robot Offline Programming software (i.e. Delmia Robotics), which allows to automatically compute energy-optimal motion parameters, for a given end-effector path, by tuning the joint speed/acceleration during point-to-point motions whenever allowed by the manufacturing constraints. The main advantage of this method, as compared to other optimization routines that are not conceived for a seamless integration with commercial industrial manipulators, is that the computed parameters are the same required by the robot controls, so that the results can generate ready-to-use energy-optimal robot code.

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