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Bouguerra, Abdelbaki
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Publications (10 of 27) Show all publications
Palm, R., Bouguerra, A., Abdullah, M. & Lilienthal, A. (2016). Navigation in Human-Robot and Robot-Robot Interaction using Optimization Methods. In: SMC 2016: 2016 IEEE International Conference on Systems, Man, and Cybernetics. Paper presented at 2016 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2016, Budapest, Hungary, October 9-12, 2016 (pp. 4489-4494). IEEE.
Open this publication in new window or tab >>Navigation in Human-Robot and Robot-Robot Interaction using Optimization Methods
2016 (English)In: SMC 2016: 2016 IEEE International Conference on Systems, Man, and Cybernetics, IEEE, 2016, 4489-4494 p.Conference paper, Published paper (Refereed)
Abstract [en]

Human-robot interaction and robot-robot interaction and cooperation in shared spatial areas is a challenging field of research regarding safety, stability and performance. In this paper the collision avoidance between human and robot by extrapolation of human intentions and a suitable optimization of tracking velocities is discussed. Furthermore for robot-robot interactions in a shared area traffic rules and artificial force potential fields and their optimization by market-based approach are applied for obstacle avoidance. For testing and verification, the navigation strategy is implemented and tested in simulation of more realistic vehicles. Extensive simulation experiments are performed to examine the improvement of the traditional potential field (PF) method by the MBO strategy.

Place, publisher, year, edition, pages
IEEE, 2016
Keyword
Human-robot interaction, human intentions, collision avoidance, robot navigation, artificial force fields, market-based optimization
National Category
Computer and Information Sciences
Research subject
Computer Science
Identifiers
urn:nbn:se:oru:diva-53702 (URN)000402634704051 ()978-1-5090-1897-0 (ISBN)
Conference
2016 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2016, Budapest, Hungary, October 9-12, 2016
Projects
AIR-project Action and Intention Recognition in Human Interaction with Autonomous Systems
Available from: 2016-12-01 Created: 2016-12-01 Last updated: 2018-01-13Bibliographically approved
Andreasson, H., Bouguerra, A., Cirillo, M., Dimitrov, D. N., Driankov, D., Karlsson, L., . . . Stoyanov, T. (2015). Autonomous transport vehicles: where we are and what is missing. IEEE robotics & automation magazine, 22(1), 64-75.
Open this publication in new window or tab >>Autonomous transport vehicles: where we are and what is missing
Show others...
2015 (English)In: IEEE robotics & automation magazine, ISSN 1070-9932, E-ISSN 1558-223X, Vol. 22, no 1, 64-75 p.Article in journal (Refereed) Published
Abstract [en]

In this article, we address the problem of realizing a complete efficient system for automated management of fleets of autonomous ground vehicles in industrial sites. We elicit from current industrial practice and the scientific state of the art the key challenges related to autonomous transport vehicles in industrial environments and relate them to enabling techniques in perception, task allocation, motion planning, coordination, collision prediction, and control. We propose a modular approach based on least commitment, which integrates all modules through a uniform constraint-based paradigm. We describe an instantiation of this system and present a summary of the results, showing evidence of increased flexibility at the control level to adapt to contingencies.

Keyword
Intelligent vehicles; Mobile robots; Resource management; Robot kinematics; Trajectory; Vehicle dynamics
National Category
Robotics
Identifiers
urn:nbn:se:oru:diva-44432 (URN)10.1109/MRA.2014.2381357 (DOI)000352030600010 ()2-s2.0-84925133099 (Scopus ID)
Available from: 2015-04-24 Created: 2015-04-24 Last updated: 2017-12-04Bibliographically approved
Mojtahedzadeh, R., Bouguerra, A., Schaffernicht, E. & Lilienthal, A. J. (2015). Support relation analysis and decision making for safe robotic manipulation tasks. Robotics and Autonomous Systems, 71(SI), 99-117.
Open this publication in new window or tab >>Support relation analysis and decision making for safe robotic manipulation tasks
2015 (English)In: Robotics and Autonomous Systems, ISSN 0921-8890, E-ISSN 1872-793X, Vol. 71, no SI, 99-117 p.Article in journal (Refereed) Published
Abstract [en]

In this article, we describe an approach to address the issue of automatically building and using high-level symbolic representations that capture physical interactions between objects in static configurations. Our work targets robotic manipulation systems where objects need to be safely removed from piles that come in random configurations. We assume that a 3D visual perception module exists so that objects in the piles can be completely or partially detected. Depending on the outcome of the perception, we divide the issue into two sub-issues: 1) all objects in the configuration are detected; 2) only a subset of objects are correctly detected. For the first case, we use notions from geometry and static equilibrium in classical mechanics to automatically analyze and extract act and support relations between pairs of objects. For the second case, we use machine learning techniques to estimate the probability of objects supporting each other. Having the support relations extracted, a decision making process is used to identify which object to remove from the configuration so that an expected minimum cost is optimized. The proposed methods have been extensively tested and validated on data sets generated in simulation and from real world configurations for the scenario of unloading goods from shipping containers.

Place, publisher, year, edition, pages
Amsterdam: Elsevier, 2015
Keyword
Scene analysis, Machine learning, Decision making, World models, Robotic manipulation
National Category
Computer Sciences
Research subject
Computer Science
Identifiers
urn:nbn:se:oru:diva-40703 (URN)10.1016/j.robot.2014.12.014 (DOI)000357146000010 ()
Projects
Cognitive Robot for Automation of Logistic Processes (RobLog)
Available from: 2015-01-10 Created: 2015-01-10 Last updated: 2018-01-11Bibliographically approved
Andreasson, H., Bouguerra, A., Åstrand, B. & Rögnvaldsson, T. (2014). Gold-Fish SLAM: An Application of SLAM to Localize AGVs. In: Yoshida, Kazuya; Tadokoro, Satoshi (Ed.), Field and Service Robotics: Results of the 8th International Conference (pp. 585-598). Heidelberg, Germany: Springer Berlin/Heidelberg.
Open this publication in new window or tab >>Gold-Fish SLAM: An Application of SLAM to Localize AGVs
2014 (English)In: Field and Service Robotics: Results of the 8th International Conference / [ed] Yoshida, Kazuya; Tadokoro, Satoshi, Heidelberg, Germany: Springer Berlin/Heidelberg, 2014, 585-598 p.Chapter in book (Refereed)
Abstract [en]

The main focus of this paper is to present a case study of a SLAM solution for Automated Guided Vehicles (AGVs) operating in real-world industrial environments. The studied solution, called Gold-fish SLAM, was implemented to provide localization estimates in dynamic industrial environments, where there are static landmarks that are only rarely perceived by the AGVs. The main idea of Gold-fish SLAM is to consider the goods that enter and leave the environment as temporary landmarks that can be used in combination with the rarely seen static landmarks to compute online estimates of AGV poses. The solution is tested and verified in a factory of paper using an eight ton diesel-truck retrofitted with an AGV control system running at speeds up to 3 m/s. The paper includes also a general discussion on how SLAM can be used in industrial applications with AGVs

Place, publisher, year, edition, pages
Heidelberg, Germany: Springer Berlin/Heidelberg, 2014
Series
Springer Tracts in Advanced Robotics, ISSN 1610-7438 ; 92
National Category
Computer Sciences
Identifiers
urn:nbn:se:oru:diva-41306 (URN)10.1007/978-3-642-40686-7_39 (DOI)2-s2.0-84897721700 (Scopus ID)978-3-642-40685-0 (ISBN)978-3-642-40686-7 (ISBN)
Projects
MALTA
Available from: 2014-08-28 Created: 2015-01-14 Last updated: 2018-01-11Bibliographically approved
Mojtahedzadeh, R., Bouguerra, A., Schaffernicht, E. & Lilienthal, A. J. (2014). Probabilistic Relational Scene Representation and Decision Making Under Incomplete Information for Robotic Manipulation Tasks. In: Robotics and Automation (ICRA), 2014 IEEE International Conference on: . Paper presented at 2014 IEEE International Conference on Robotics and Automation (ICRA 2014, Hong Kong, China, May 31 - June 7, 2014 (pp. 5685-5690). IEEE Robotics and Automation Society.
Open this publication in new window or tab >>Probabilistic Relational Scene Representation and Decision Making Under Incomplete Information for Robotic Manipulation Tasks
2014 (English)In: Robotics and Automation (ICRA), 2014 IEEE International Conference on, IEEE Robotics and Automation Society, 2014, 5685-5690 p.Conference paper, Published paper (Refereed)
Abstract [en]

In this paper, we propose an approach for robotic manipulation systems to autonomously reason about their environments under incomplete information. The target application is to automate the task of unloading the content of shipping containers. Our goal is to capture possible support relations between objects in partially known static configurations. We employ support vector machines (SVM) to estimate the probability of a support relation between pairs of detected objects using features extracted from their geometrical properties and 3D sampled points of the scene. The set of probabilistic support relations is then used for reasoning about optimally selecting an object to be unloaded first. The proposed approach has been extensively tested and verified on data sets generated in simulation and from real world configurations.

Place, publisher, year, edition, pages
IEEE Robotics and Automation Society, 2014
Series
IEEE International Conference on Robotics and Automation ICRA, ISSN 1050-4729
Keyword
Containers, Manipulators, Industrial Robots, Object Detection, Support Vector Machines, Decision Making
National Category
Computer Sciences
Research subject
Computer Science
Identifiers
urn:nbn:se:oru:diva-40693 (URN)10.1109/ICRA.2014.6907695 (DOI)000377221105109 ()2-s2.0-84929208915 (Scopus ID)978-1-4799-3685-4 (ISBN)
Conference
2014 IEEE International Conference on Robotics and Automation (ICRA 2014, Hong Kong, China, May 31 - June 7, 2014
Projects
Cognitive Robot for Automation of Logistic Processes (RobLog)
Available from: 2015-01-10 Created: 2015-01-10 Last updated: 2018-01-11Bibliographically approved
Mojtahedzadeh, R., Bouguerra, A. & Lilienthal, A. J. (2013). Automatic relational scene representation for safe robotic manipulation tasks. In: : . Paper presented at Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) (pp. 1335-1340). IEEE.
Open this publication in new window or tab >>Automatic relational scene representation for safe robotic manipulation tasks
2013 (English)Conference paper, Published paper (Refereed)
Abstract [en]

In this paper, we propose a new approach forautomatically building symbolic relational descriptions of staticconfigurations of objects to be manipulated by a robotic system.The main goal of our work is to provide advanced cognitiveabilities for such robotic systems to make them more aware ofthe outcome of their actions. We describe how such symbolicrelations are automatically extracted for configurations ofbox-shaped objects using notions from geometry and staticequilibrium in classical mechanics. We also present extensivesimulation results as well as some real-world experiments aimedat verifying the output of the proposed approach.

Place, publisher, year, edition, pages
IEEE, 2013
Series
IEEE International Conference on Intelligent Robots and Systems, ISSN 2153-0858
National Category
Robotics Computer Sciences
Research subject
Computer Science
Identifiers
urn:nbn:se:oru:diva-32395 (URN)10.1109/IROS.2013.6696522 (DOI)000331367401064 ()2-s2.0-84893791900 (Scopus ID)978-1-4673-6358-7 (ISBN)
Conference
Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)
Available from: 2013-11-14 Created: 2013-11-14 Last updated: 2018-01-11Bibliographically approved
Palm, R. & Bouguerra, A. (2013). Particle swarm against market-based optimisation for obstacle avoidance. Electronics Letters, 49(22), 1378-1379.
Open this publication in new window or tab >>Particle swarm against market-based optimisation for obstacle avoidance
2013 (English)In: Electronics Letters, ISSN 0013-5194, E-ISSN 1350-911X, Vol. 49, no 22, 1378-1379 p.Article in journal (Refereed) Published
Abstract [en]

A comparison of particle swarm optimisation (PSO) and market-based optimisation (MBO) is presented when applied to obstacle avoidance by mobile robots using artificial potential fields and special traffic rules. Most notably, PSO and MBO are applied to optimise the motion of mobile robots when acting in a common confined workspace. Simulation results show that both methods perform equally well with slight advantage for PSO.

Keyword
collision avoidance, mobile robots, particle swarm optimisation, market-based optimisation, obstacle avoidance, MBO, PSO, artificial potential fields, traffic rules, mobile robot motion optimisation
National Category
Engineering and Technology
Identifiers
urn:nbn:se:oru:diva-32534 (URN)10.1049/el.2013.2663 (DOI)000326178000011 ()
Available from: 2013-11-26 Created: 2013-11-26 Last updated: 2017-12-06Bibliographically approved
Palm, R. & Bouguerra, A. (2013). Particle swarm optimization of potential fields for obstacle avoidance. In: Scientific cooperations Intern. Conf. in Electrical and Electronics Engineering: . Paper presented at Recent Advances in Robotics and Mechatronics (pp. 117-123). .
Open this publication in new window or tab >>Particle swarm optimization of potential fields for obstacle avoidance
2013 (English)In: Scientific cooperations Intern. Conf. in Electrical and Electronics Engineering, 2013, 117-123 p.Conference paper, Published paper (Refereed)
Abstract [en]

This paper addresses the safe navigation of multiple nonholonomic mobile robots in shared areas. Obstacle avoidance for mobile robots is performed by artificial potential fields and special traffic rules. In addition, the behavior of mobile robots is optimized by particle swarm optimization (PSO). The control of non-holonomic vehicles is performed using the virtual leader principle together with a local linear controller.

Keyword
Mobile robots, obstacle avoidance, potential field, particle swarm optimization
National Category
Computer Sciences
Identifiers
urn:nbn:se:oru:diva-30907 (URN)
Conference
Recent Advances in Robotics and Mechatronics
Available from: 2013-09-20 Created: 2013-09-20 Last updated: 2018-01-11Bibliographically approved
Andreasson, H., Bouguerra, A., Åstrand, B. & Rögnvaldsson, T. (2012). Gold-fish SLAM: an application of SLAM to localize AGVs. In: Proceedings of the International Conference on Field and Service Robotics (FSR), July 2012.: . Paper presented at International Conference on Field and Service Robotics (FSR), July 2012.. .
Open this publication in new window or tab >>Gold-fish SLAM: an application of SLAM to localize AGVs
2012 (English)In: Proceedings of the International Conference on Field and Service Robotics (FSR), July 2012., 2012Conference paper, Published paper (Other academic)
Abstract [en]

The main focus of this paper is to present a case study of a SLAM solution for Automated Guided Vehicles (AGVs) operating in real-world industrial environ- ments. The studied solution, called Gold-fish SLAM, was implemented to provide localization estimates in dynamic industrial environments, where there are static landmarks that are only rarely perceived by the AGVs. The main idea of Gold-fish SLAM is to consider the goods that enter and leave the environment as temporary landmarks that can be used in combination with the rarely seen static landmarks to compute online estimates of AGV poses. The solution is tested and verified in a factory of paper using an eight ton diesel-truck retrofitted with an AGV control sys- tem running at speeds up to 3 meters per second. The paper includes also a general discussion on how SLAM can be used in industrial applications with AGVs.

Keyword
Mobile robotics, AGV localization
National Category
Computer Sciences
Research subject
Computer and Systems Science; Computer Science
Identifiers
urn:nbn:se:oru:diva-10393 (URN)
Conference
International Conference on Field and Service Robotics (FSR), July 2012.
Available from: 2010-04-19 Created: 2010-04-19 Last updated: 2018-01-12Bibliographically approved
Palm, R. & Abdelbaki, B. (2012). Market-based algorithms and fuzzy methods for the navigation of mobile robots. In: : . Paper presented at IEEE International Conference on Fuzzy Systems (FUZZ-IEEE), 2012 (pp. 1-8). IEEE conference proceedings.
Open this publication in new window or tab >>Market-based algorithms and fuzzy methods for the navigation of mobile robots
2012 (English)Conference paper, Published paper (Refereed)
Abstract [en]

An important aspect of the navigation of mobile robots is the avoidance of static and dynamic obstacles. This paper deals with obstacle avoidance using artificial potential fields and selected traffic rules. The potential field method is optimized by a mixture of fuzzy methods and market-based optimization (MBO) between competing potential fields of mobile robots. Here, depending on the local situation, some potential fields are strengthened and some are weakened. The optimization takes place especially when several mobile robots act in a small area. In addition, to avoid an undesired behavior of the mobile platform in the vicinity of obstacles, central symmetrical potential fields are `deformed' by using fuzzy rules.

Place, publisher, year, edition, pages
IEEE conference proceedings, 2012
Keyword
collision avoidance, fuzzy set theory, mobile robots, optimisation, MBO, artificial potential fields, dynamic obstacle avoidance
National Category
Robotics
Research subject
Computer Science; Electrical Engineering
Identifiers
urn:nbn:se:oru:diva-28822 (URN)10.1109/FUZZ-IEEE.2012.6251228 (DOI)000309188200165 ()978-1-4673-1507-4 (ISBN)
Conference
IEEE International Conference on Fuzzy Systems (FUZZ-IEEE), 2012
Note

Rainer Palm is Adjunct Professor at the Department of Technology (AASS), University Örebro since 2004

Available from: 2013-04-25 Created: 2013-04-25 Last updated: 2017-10-18Bibliographically approved
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