Task scheduling and motion planning for an industrial manipulator

Zacharia, Paraskevi Th.; Xidias, Elias K.; Aspragathos, Nikos Α.

doi:10.1016/j.rcim.2013.05.002

Cited by 47 publications

(40 citation statements)

References 10 publications

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“…On a task with 3-DoF and 6-DoF robots involving 50 targets, a near-optimal solution is found in 1, 800 s. The quality of the solution depends on several control parameters (related to the GA) and the number of iterations. This approach has been further extended to include collision-free path planning for 2D and 3D environments [8], [9].…”

Section: Related Workmentioning

confidence: 99%

RoboTSP – A Fast Solution to the Robotic Task Sequencing Problem

Suárez-Ruiz

Lembono

Pham

2018

2018 IEEE International Conference on Robotics and Automation (ICRA)

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In many industrial robotics applications, such as spot-welding, spray-painting or drilling, the robot is required to visit successively multiple targets. The robot travel time among the targets is a significant component of the overall execution time. This travel time is in turn greatly affected by the order of visit of the targets, and by the robot configurations used to reach each target. Therefore, it is crucial to optimize these two elements, a problem known in the literature as the Robotic Task Sequencing Problem (RTSP). Our contribution in this paper is two-fold. First, we propose a fast, near-optimal, algorithm to solve RTSP. The key to our approach is to exploit the classical distinction between task space and configuration space, which, surprisingly, has been so far overlooked in the RTSP literature. Second, we provide an open-source implementation of the above algorithm, which has been carefully benchmarked to yield an efficient, ready-to-use, software solution. We discuss the relationship between RTSP and other Traveling Salesman Problem (TSP) variants, such as the Generalized Traveling Salesman Problem (GTSP), and show experimentally that our method finds motion sequences of the same quality but using several orders of magnitude less computation time than existing approaches.

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Section: Related Workmentioning

confidence: 99%

RoboTSP – A Fast Solution to the Robotic Task Sequencing Problem

Suárez-Ruiz

Lembono

Pham

2018

2018 IEEE International Conference on Robotics and Automation (ICRA)

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“…Task scheduling [19] of the proposed system is shown in Figure 5. The robot controller will ask the grab-side control unit for the grabbing coordinates.…”

Section: System Composition and Designmentioning

confidence: 99%

An Automatic Assembling System for Sealing Rings Based on Machine Vision

Gao

Xiao

et al. 2017

Journal of Sensors

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In order to grab and place the sealing rings of battery lid quickly and accurately, an automatic assembling system for sealing rings based on machine vision is developed in this paper. The whole system is composed of the light sources, cameras, industrial control units, and a 4-degree-of-freedom industrial robot. Specifically, the sealing rings are recognized and located automatically with the machine vision module. Then industrial robot is controlled for grabbing the sealing rings dynamically under the joint work of multiple control units and visual feedback. Furthermore, the coordinates of the fast-moving battery lid are tracked by the machine vision module. Finally the sealing rings are placed on the sealing ports of battery lid accurately and automatically. Experimental results demonstrate that the proposed system can grab the sealing rings and place them on the sealing port of the fast-moving battery lid successfully. More importantly, the proposed system can improve the efficiency of the battery production line obviously.

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“…Industrial robots play a key role for industrial automation and process consistency [1]. In today best practice robot programs are developed off-line using CAD/CAM simulation suits, such as Delmia, RobCAD, etc., to compute collision free robot trajectory [2]. Though those practices are still a premium solution to model and simulate production systems, they are unable to find the optimal solution subject to multiple attributes.…”

Section: Introductionmentioning

confidence: 99%

“…We aim to maximize the reachability; A4collision: robot movement must be collision free. Robot programming is usually decomposed in four subproblems/steps [2], [7]:…”

Section: Introductionmentioning

confidence: 99%