Room: G29, R308
Phone: +39 391 67 52662
Sergey graduated from Chita State University (was renamed in 2012 to Transbaikal State University) in June 2011 with Diploma of Engineer. Since July he is working in CSE team on his PhD. Dissertation theme covers problems of industrial robot task sequence optimization.
For more information about Sergey Alatartsev visit his personal homepage.
Research domains
- Traveling Salesman Problem with Neighborhoods
- Improving the Sequence of Robotic Tasks with Freedom of Execution
Sergey Alatartsev
Publications
2015 |
Alatartsev, Sergey Robot Trajectory Optimization for Relaxed Effective Tasks Promotionsarbeit Otto-von-Guericke University of Magdeburg, 2015. @phdthesis{Alatartsev2015c, title = {Robot Trajectory Optimization for Relaxed Effective Tasks}, author = {Sergey Alatartsev}, url = {https://cse.cs.ovgu.de/cse-wordpress/wp-content/uploads/2016/01/Alatartsev_PhD_thesis.pdf}, year = {2015}, date = {2015-07-07}, school = {Otto-von-Guericke University of Magdeburg}, abstract = {Industrial robots are flexible machines that are currently involved in multiple production domains. Mainly their workflow consists of two alternating stages. The first stage is effective movements that are required to perform a task, e.g., welding a seam. The second stage is supporting movements that are needed to move from one effective task to another, e.g., movements between welding seams. Many effective tasks allow a certain freedom during their execution, e.g., the robot’s tool might have a certain deviation during welding. This freedom is often ignored and robots are programmed manually based on the programmer’s intuition. Nonetheless, this freedom can be used as an extra degree of freedom for robot trajectory optimization. In this thesis, we propose a formalization of this freedom for effective tasks. We refer to an effective task with a formalized freedom of execution as a relaxed effective task. Having an infinite number of ways to execute a task raises several research questions: (i) how to optimize a sequence of entry points for relaxed effective tasks? (ii) how to find starting robot configurations for these tasks? (iii) how to optimize a robot trajectory for a certain relaxed task? We propose a solution concept that decomposes a problem containing all three questions into three components that can be applied in combination with each other or with other state-of-the-art approaches. The first component considers the problem of finding a sequence of effective tasks and their entry points. This problem is modeled as the Traveling Salesman Problem with Neighborhoods (TSPN) where a tour has to be found through a set of areas. We propose a Constricting Insertion Heuristic for constructing a tour and a Constricting 3-Opt for improving the tour. In the second component, the problem of adapting a tour for a robot to execute and searching for starting robot configurations is modeled as a Touring-a-sequence-of-Polygons Problem (TPP) where a tour has to be found through a given sequence of areas. We propose a modification of the Rubber-Band Algorithm (RBA). We refer to this extension as a Nested RBA. Optimization of a robot trajectory in the third component is also represented as a TPP. However, in contrast to the classic RBA where areas are constricted with a polyline, we propose an extension of the RBA called Smoothed RBA where areas are constricted with a smooth curve which leads to a minimal cost robot trajectory. }, keywords = {}, pubstate = {published}, tppubtype = {phdthesis} } Industrial robots are flexible machines that are currently involved in multiple production domains. Mainly their workflow consists of two alternating stages. The first stage is effective movements that are required to perform a task, e.g., welding a seam. The second stage is supporting movements that are needed to move from one effective task to another, e.g., movements between welding seams. Many effective tasks allow a certain freedom during their execution, e.g., the robot’s tool might have a certain deviation during welding. This freedom is often ignored and robots are programmed manually based on the programmer’s intuition. Nonetheless, this freedom can be used as an extra degree of freedom for robot trajectory optimization. In this thesis, we propose a formalization of this freedom for effective tasks. We refer to an effective task with a formalized freedom of execution as a relaxed effective task. Having an infinite number of ways to execute a task raises several research questions: (i) how to optimize a sequence of entry points for relaxed effective tasks? (ii) how to find starting robot configurations for these tasks? (iii) how to optimize a robot trajectory for a certain relaxed task? We propose a solution concept that decomposes a problem containing all three questions into three components that can be applied in combination with each other or with other state-of-the-art approaches. The first component considers the problem of finding a sequence of effective tasks and their entry points. This problem is modeled as the Traveling Salesman Problem with Neighborhoods (TSPN) where a tour has to be found through a set of areas. We propose a Constricting Insertion Heuristic for constructing a tour and a Constricting 3-Opt for improving the tour. In the second component, the problem of adapting a tour for a robot to execute and searching for starting robot configurations is modeled as a Touring-a-sequence-of-Polygons Problem (TPP) where a tour has to be found through a given sequence of areas. We propose a modification of the Rubber-Band Algorithm (RBA). We refer to this extension as a Nested RBA. Optimization of a robot trajectory in the third component is also represented as a TPP. However, in contrast to the classic RBA where areas are constricted with a polyline, we propose an extension of the RBA called Smoothed RBA where areas are constricted with a smooth curve which leads to a minimal cost robot trajectory. |
Alatartsev, Sergey; Stellmacher, Sebastian; Ortmeier, Frank Robotic Task Sequencing Problem: A Survey Artikel Journal of Intelligent and Robotic Systems, 2015, ISSN: 1573-0409. @article{Alatartsev2015, title = {Robotic Task Sequencing Problem: A Survey}, author = { Sergey Alatartsev and Sebastian Stellmacher and Frank Ortmeier}, url = {http://link.springer.com/article/10.1007/s10846-015-0190-6 https://cse.cs.ovgu.de/cse-wordpress/wp-content/uploads/2015/05/Alatartsev_JIRS2015.pdf}, doi = {10.1007/s10846-015-0190-6}, issn = {1573-0409}, year = {2015}, date = {2015-01-01}, booktitle = {Journal of Intelligent and Robotic Systems}, journal = {Journal of Intelligent and Robotic Systems}, publisher = {Springer}, abstract = {Today, robotics is an important cornerstone of modern industrial production. Robots are used for numerous reasons including reliability and continuously high quality of work. The main decision factor is the overall efficiency of the robotic system in the production line. One key issue for this is the optimality of the whole set of robotic movements for industrial applications, which typically consist of multiple atomic tasks such as welding seams, drilling holes, etc. Currently, in many industrial scenarios such movements are optimized manually. This is costly and error-prone. Therefore, researchers have been working on algorithms for automatic computation of optimal trajectories for several years. This problem gets even more complicated due to multiple additional factors like redundant kinematics, collision avoidance, possibilities of ambiguous task performance, etc. This survey article summarizes and categorizes the approaches for optimization of the robotic task sequence. It provides an overview of existing combinatorial problems that are applied for robot task sequencing. It also highlights the strengths and the weaknesses of existing approaches as well as the challenges for future research in this domain. The article is meant for both scientists and practitioners. For scientists, it provides an overview on applied algorithmic approaches. For practitioners, it presents existing solutions, which are categorized according to the classes of input and output parameters.}, keywords = {}, pubstate = {published}, tppubtype = {article} } Today, robotics is an important cornerstone of modern industrial production. Robots are used for numerous reasons including reliability and continuously high quality of work. The main decision factor is the overall efficiency of the robotic system in the production line. One key issue for this is the optimality of the whole set of robotic movements for industrial applications, which typically consist of multiple atomic tasks such as welding seams, drilling holes, etc. Currently, in many industrial scenarios such movements are optimized manually. This is costly and error-prone. Therefore, researchers have been working on algorithms for automatic computation of optimal trajectories for several years. This problem gets even more complicated due to multiple additional factors like redundant kinematics, collision avoidance, possibilities of ambiguous task performance, etc. This survey article summarizes and categorizes the approaches for optimization of the robotic task sequence. It provides an overview of existing combinatorial problems that are applied for robot task sequencing. It also highlights the strengths and the weaknesses of existing approaches as well as the challenges for future research in this domain. The article is meant for both scientists and practitioners. For scientists, it provides an overview on applied algorithmic approaches. For practitioners, it presents existing solutions, which are categorized according to the classes of input and output parameters. |
2014 |
Alatartsev, Sergey; Belov, Anton; Nykolaichuk, Mykhaylo; Ortmeier, Frank Robot Trajectory Optimization for the Relaxed End-Effector Path Inproceedings Proceedings of the 11th International Conference on Informatics in Control, Automation and Robotics (ICINCO), 2014. @inproceedings{Alatartsev2014_1, title = {Robot Trajectory Optimization for the Relaxed End-Effector Path}, author = { Sergey Alatartsev and Anton Belov and Mykhaylo Nykolaichuk and Frank Ortmeier}, url = {https://cse.cs.ovgu.de/cse-wordpress/wp-content/uploads/2015/05/Alatartsev_ICINCO2014.pdf}, year = {2014}, date = {2014-01-01}, booktitle = {Proceedings of the 11th International Conference on Informatics in Control, Automation and Robotics (ICINCO)}, abstract = {In this paper we consider the trajectory optimization problem for the effective tasks performed by industrial robots, e.g., welding, cutting or camera inspection. The distinctive feature of such tasks is that a robot has to follow a certain end-effector path with its motion law. For example, welding a line with a certain velocity has an even influence on the surface. The end-effector path and its motion law depend on the industrial process requirements. They are calculated without considering robot kinematics, hence, are often “awkward” for the robot execution, e.g., cause high jerks in the robot’s joints. In this paper we present the trajectory optimization problem where the end-effector path is allowed to have a certain deviation. Such path is referred to as relaxed path. The goal of the paper is to make use of this freedom and construct the minimal-cost robot trajectory. To demonstrate the potential of the problem, jerk of the robot joint trajectory was minimized.}, keywords = {}, pubstate = {published}, tppubtype = {inproceedings} } In this paper we consider the trajectory optimization problem for the effective tasks performed by industrial robots, e.g., welding, cutting or camera inspection. The distinctive feature of such tasks is that a robot has to follow a certain end-effector path with its motion law. For example, welding a line with a certain velocity has an even influence on the surface. The end-effector path and its motion law depend on the industrial process requirements. They are calculated without considering robot kinematics, hence, are often “awkward” for the robot execution, e.g., cause high jerks in the robot’s joints. In this paper we present the trajectory optimization problem where the end-effector path is allowed to have a certain deviation. Such path is referred to as relaxed path. The goal of the paper is to make use of this freedom and construct the minimal-cost robot trajectory. To demonstrate the potential of the problem, jerk of the robot joint trajectory was minimized. |
Alatartsev, Sergey; Ortmeier, Frank Improving the Sequence of Robotic Tasks with Freedom of Execution Inproceedings IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2014. @inproceedings{Alatartsev2014, title = {Improving the Sequence of Robotic Tasks with Freedom of Execution}, author = { Sergey Alatartsev and Frank Ortmeier}, url = {https://cse.cs.ovgu.de/cse-wordpress/wp-content/uploads/2015/05/Alatartsev_IROS2014.pdf}, year = {2014}, date = {2014-01-01}, booktitle = {IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)}, abstract = {An industrial robot’s workflow typically consists of a set of tasks that have to be repeated multiple times. A task could be, for example, welding a seam or cutting a hole. The efficiency with which the robot performs the sequence of tasks is an important factor in most production domains. The more often a set of tasks can be performed by a robot the more advantages it provides to the company. In most practical scenarios, the majority of tasks have a certain freedom of execution. For example, closed-contour welding task can often be started and finished at any point of the curve. Also the exact orientation of the welding torch is not fixed, but may be in a certain range, e.g., between 85◦ and 95◦ . Currently, these degrees of freedom are used to manually generate robot trajectories. However, their quality highly depends on skills and experience of the robot programmer. In this paper we propose a method that is able to automatically improve the given sequence of robotic tasks by adding certain freedom to (i) the position of the starting point along the curve, (ii) the orientation of the end-effector and (iii) the robot configuration. The proposed approach does not depend on the production domain and could be combined with any algorithm for constructing the initial task sequence. We evaluate the algorithm on a realistic case study and show that it could significantly improve the production time on the test instances from the cutting-deburring domain.}, keywords = {}, pubstate = {published}, tppubtype = {inproceedings} } An industrial robot’s workflow typically consists of a set of tasks that have to be repeated multiple times. A task could be, for example, welding a seam or cutting a hole. The efficiency with which the robot performs the sequence of tasks is an important factor in most production domains. The more often a set of tasks can be performed by a robot the more advantages it provides to the company. In most practical scenarios, the majority of tasks have a certain freedom of execution. For example, closed-contour welding task can often be started and finished at any point of the curve. Also the exact orientation of the welding torch is not fixed, but may be in a certain range, e.g., between 85◦ and 95◦ . Currently, these degrees of freedom are used to manually generate robot trajectories. However, their quality highly depends on skills and experience of the robot programmer. In this paper we propose a method that is able to automatically improve the given sequence of robotic tasks by adding certain freedom to (i) the position of the starting point along the curve, (ii) the orientation of the end-effector and (iii) the robot configuration. The proposed approach does not depend on the production domain and could be combined with any algorithm for constructing the initial task sequence. We evaluate the algorithm on a realistic case study and show that it could significantly improve the production time on the test instances from the cutting-deburring domain. |
2013 |
Alatartsev, Sergey; Augustine, Marcus; Ortmeier, Frank Constricting Insertion Heuristic for Traveling Salesman Problem with Neighborhoods Inproceedings Proceedings of the 23rd International Conference on Automated Planning and Scheduling (ICAPS-2013), AAAI, 2013. @inproceedings{ICAPS13, title = {Constricting Insertion Heuristic for Traveling Salesman Problem with Neighborhoods}, author = { Sergey Alatartsev and Marcus Augustine and Frank Ortmeier}, url = {https://cse.cs.ovgu.de/cse-wordpress/wp-content/uploads/2015/05/Alatartsev_ICAPS2013.pdf https://www.youtube.com/watch?v=oT9ngCfLFq8}, year = {2013}, date = {2013-01-01}, booktitle = {Proceedings of the 23rd International Conference on Automated Planning and Scheduling (ICAPS-2013)}, publisher = {AAAI}, abstract = {Sequence optimization is an important problem in many production automation scenarios involving industrial robots. Mostly, this is done by reducing it to Traveling Salesman Problem (TSP). However, in many industrial scenarios optimization potential is not only hidden in optimizing a sequence of operations but also in optimizing the individual operations themselves. From a formal point of view, this leads to the Traveling Salesman Problem with Neighborhoods (TSPN). TSPN is a generalization of TSP where areas should be visited instead of points. In this paper we propose a new method for solving TSPN efficiently. We compare the new method to the related approaches using existing test benchmarks from the literature. According to the evaluation on instances with known optimal values, our method is able to obtain a solution close to the optimum. }, keywords = {}, pubstate = {published}, tppubtype = {inproceedings} } Sequence optimization is an important problem in many production automation scenarios involving industrial robots. Mostly, this is done by reducing it to Traveling Salesman Problem (TSP). However, in many industrial scenarios optimization potential is not only hidden in optimizing a sequence of operations but also in optimizing the individual operations themselves. From a formal point of view, this leads to the Traveling Salesman Problem with Neighborhoods (TSPN). TSPN is a generalization of TSP where areas should be visited instead of points. In this paper we propose a new method for solving TSPN efficiently. We compare the new method to the related approaches using existing test benchmarks from the literature. According to the evaluation on instances with known optimal values, our method is able to obtain a solution close to the optimum. |
Alatartsev, Sergey; Mersheeva, Vera; Augustine, Marcus; Ortmeier, Frank On Optimizing a Sequence of Robotic Tasks Inproceedings Proceedings of the International Conference on Intelligent Robots and Systems (IROS), IEEE, 2013. @inproceedings{IROS2013, title = {On Optimizing a Sequence of Robotic Tasks}, author = { Sergey Alatartsev and Vera Mersheeva and Marcus Augustine and Frank Ortmeier}, url = {https://cse.cs.ovgu.de/cse-wordpress/wp-content/uploads/2015/05/Alatartsev_IROS2013.pdf}, year = {2013}, date = {2013-01-01}, booktitle = {Proceedings of the International Conference on Intelligent Robots and Systems (IROS)}, publisher = {IEEE}, abstract = {Production speed and energy efficiency are crucial factors for any application scenario in industrial robotics. The most important factor for this is planning of an optimized sequence of atomic subtasks. In a welding scenario, an atomic subtask could be understood as a single welding seam/spot while the sequence could be the ordering of these atomic tasks. Optimization of a task sequence is normally modeled as the Traveling Salesman Problem (TSP). This works well for simple scenarios with atomic tasks without execution freedom like spot welding. However, many types of tasks allow a certain freedom of execution. A simple example is seam welding of a closed-contour, where typically the starting-ending point is not specified by the application. This extra degree of freedom allows for much more efficient task sequencing. In this paper, we describe an extension of TSP to model a problem of finding an optimal sequence of tasks with such extra degree of freedom. We propose a new, efficient heuristic to solve such problems and show its applicability. Obtained computational results are close to the optimum on small instances and outperforms the state of the art approaches on benchmarks available in literature.}, keywords = {}, pubstate = {published}, tppubtype = {inproceedings} } Production speed and energy efficiency are crucial factors for any application scenario in industrial robotics. The most important factor for this is planning of an optimized sequence of atomic subtasks. In a welding scenario, an atomic subtask could be understood as a single welding seam/spot while the sequence could be the ordering of these atomic tasks. Optimization of a task sequence is normally modeled as the Traveling Salesman Problem (TSP). This works well for simple scenarios with atomic tasks without execution freedom like spot welding. However, many types of tasks allow a certain freedom of execution. A simple example is seam welding of a closed-contour, where typically the starting-ending point is not specified by the application. This extra degree of freedom allows for much more efficient task sequencing. In this paper, we describe an extension of TSP to model a problem of finding an optimal sequence of tasks with such extra degree of freedom. We propose a new, efficient heuristic to solve such problems and show its applicability. Obtained computational results are close to the optimum on small instances and outperforms the state of the art approaches on benchmarks available in literature. |
Alatartsev, Sergey; Ortmeier, Frank Path Planning for Industrial Robots Among Multiple Underspecified Tasks Inproceedings Proceedings of the Magdeburger-Informatik-Tage 2. Doktorandentagung (MIT), 2013. @inproceedings{MIT2013, title = {Path Planning for Industrial Robots Among Multiple Underspecified Tasks}, author = {Sergey Alatartsev and Frank Ortmeier}, url = {https://cse.cs.ovgu.de/cse-wordpress/wp-content/uploads/2015/05/Alatartsev_DoctoralDay2013.pdf}, year = {2013}, date = {2013-01-01}, booktitle = {Proceedings of the Magdeburger-Informatik-Tage 2. Doktorandentagung (MIT)}, abstract = {This paper is an overview of the currently going PhD project. The main goal of the project is to optimize a sequence of industrial robotic tasks. We want to make use of the fact that robotic tasks often allow some freedom during the execution. In contrast, this extra freedom is ignored by state-of-the-art approaches. This work refers to extra freedom as under-specification. This paper presents a comprehensive overview of the state-of-the-art approaches in task sequencing. We state the thesis goals and make a short introduction to the methods developed within the PhD project. Work packages are formed based on the list of unaccomplished goals. }, keywords = {}, pubstate = {published}, tppubtype = {inproceedings} } This paper is an overview of the currently going PhD project. The main goal of the project is to optimize a sequence of industrial robotic tasks. We want to make use of the fact that robotic tasks often allow some freedom during the execution. In contrast, this extra freedom is ignored by state-of-the-art approaches. This work refers to extra freedom as under-specification. This paper presents a comprehensive overview of the state-of-the-art approaches in task sequencing. We state the thesis goals and make a short introduction to the methods developed within the PhD project. Work packages are formed based on the list of unaccomplished goals. |
2012 |
Alatartsev, Sergey; Güdemann, Matthias; Ortmeier, Frank Trajectory Description Conception for Industrial Robots Konferenz 7th German Conference on Robotics (ROBOTIK 2012), Munich, Germany, 2012. @conference{Robotik2012, title = {Trajectory Description Conception for Industrial Robots}, author = { Sergey Alatartsev and Matthias G\"{u}demann and Frank Ortmeier}, url = {https://cse.cs.ovgu.de/cse-wordpress/wp-content/uploads/2015/05/Alatartsev_Robotik2012.pdf}, year = {2012}, date = {2012-01-01}, booktitle = {7th German Conference on Robotics (ROBOTIK 2012)}, pages = {365-370}, address = {Munich, Germany}, abstract = {In this paper we observe the difficulties one can face when using different MPLs (Motion Planning Library) in a single application, and propose a new conception and a language which goal is to solve these problems. The idea is to present an interface between robot programming instruments and MPLs. Our goal is to provide a powerful tool for developers of software approaches for programming industrial robots that would allow an easy combination of different MPLs in one application. In addition the proposed conception hides the inner structure of libraries and eliminates the need to investigate algorithms before applying. That would increase the speed and the quality of the newly developed software systems.}, keywords = {}, pubstate = {published}, tppubtype = {conference} } In this paper we observe the difficulties one can face when using different MPLs (Motion Planning Library) in a single application, and propose a new conception and a language which goal is to solve these problems. The idea is to present an interface between robot programming instruments and MPLs. Our goal is to provide a powerful tool for developers of software approaches for programming industrial robots that would allow an easy combination of different MPLs in one application. In addition the proposed conception hides the inner structure of libraries and eliminates the need to investigate algorithms before applying. That would increase the speed and the quality of the newly developed software systems. |