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Palm, Rainer
Publications (10 of 36) Show all publications
Chadalavada, R. T., Andreasson, H., Schindler, M., Palm, R. & Lilienthal, A. (2018). Accessing your navigation plans! Human-Robot Intention Transfer using Eye-Tracking Glasses. In: Case K. &Thorvald P. (Ed.), Advances in Manufacturing Technology XXXII: Proceedings of the 16th International Conference on Manufacturing Research, incorporating the 33rd National Conference on Manufacturing Research, September 11–13, 2018, University of Skövde, Sweden. Paper presented at 16th International Conference on Manufacturing Research, incorporating the 33rd National Conference on Manufacturing Research, University of Skövde, Sweden, September 11–13, 2018 (pp. 253-258). Amsterdam, Netherlands: IOS Press
Open this publication in new window or tab >>Accessing your navigation plans! Human-Robot Intention Transfer using Eye-Tracking Glasses
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2018 (English)In: Advances in Manufacturing Technology XXXII: Proceedings of the 16th International Conference on Manufacturing Research, incorporating the 33rd National Conference on Manufacturing Research, September 11–13, 2018, University of Skövde, Sweden / [ed] Case K. &Thorvald P., Amsterdam, Netherlands: IOS Press, 2018, p. 253-258Conference paper, Published paper (Refereed)
Abstract [en]

Robots in human co-habited environments need human-aware task and motion planning, ideally responding to people’s motion intentions as soon as they can be inferred from human cues. Eye gaze can convey information about intentions beyond trajectory and head pose of a person. Hence, we propose eye-tracking glasses as safety equipment in industrial environments shared by humans and robots. This paper investigates the possibility of human-to-robot implicit intention transference solely from eye gaze data.  We present experiments in which humans wearing eye-tracking glasses encountered a small forklift truck under various conditions. We evaluate how the observed eye gaze patterns of the participants related to their navigation decisions. Our analysis shows that people primarily gazed on that side of the robot they ultimately decided to pass by. We discuss implications of these results and relate to a control approach that uses human eye gaze for early obstacle avoidance.

Place, publisher, year, edition, pages
Amsterdam, Netherlands: IOS Press, 2018
Series
Advances in Transdisciplinary Engineering, ISSN 2352-751X, E-ISSN 2352-7528
Keywords
Human-Robot Interaction (HRI), Eye-tracking, Eye-Tracking Glasses, Navigation Intent, Implicit Intention Transference, Obstacle avoidance.
National Category
Computer Sciences
Research subject
Computer Science
Identifiers
urn:nbn:se:oru:diva-70706 (URN)10.3233/978-1-61499-902-7-253 (DOI)2-s2.0-85057390000 (Scopus ID)978-1-61499-901-0 (ISBN)978-1-61499-902-7 (ISBN)
Conference
16th International Conference on Manufacturing Research, incorporating the 33rd National Conference on Manufacturing Research, University of Skövde, Sweden, September 11–13, 2018
Projects
Action and Intention Recognition (AIR)ILIAD
Available from: 2018-12-12 Created: 2018-12-12 Last updated: 2018-12-18Bibliographically approved
Palm, R. & Lilienthal, A. (2018). Fuzzy logic and control in Human-Robot Systems: geometrical and kinematic considerations. In: IEEE (Ed.), WCCI 2018: 2018 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE). Paper presented at FUZZ-IEEE 2018, Rio de Janeiro, Brazil, 8-13 July, 2018 (pp. 827-834). IEEE
Open this publication in new window or tab >>Fuzzy logic and control in Human-Robot Systems: geometrical and kinematic considerations
2018 (English)In: WCCI 2018: 2018 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE) / [ed] IEEE, IEEE, 2018, p. 827-834Conference paper, Published paper (Refereed)
Abstract [en]

The interaction between humans and mobile robots in shared areas requires adequate control for both humans and robots.The online path planning of the robot depending on the estimated or intended movement of the person is crucial for the obstacle avoidance and close cooperation between them. The velocity obstacles method and its fuzzification optimizes the relationship between the velocities of a robot and a human agent during the interaction. In order to find the estimated intersection between robot and human in the case of positions/orientations disturbed by noise, analytical and fuzzified versions are presented. The orientation of a person is estimated by eye tracking, with the help of which the intersection area is calculated. Eye tracking leads to clusters of fixations that are condensed into cluster centers by fuzzy-time clustering to detect the intention and attention of humans.

Place, publisher, year, edition, pages
IEEE, 2018
Keywords
Human-robot interaction, fuzzy control, obstacle avoidance, eye tracking
National Category
Robotics
Research subject
Human-Computer Interaction
Identifiers
urn:nbn:se:oru:diva-68021 (URN)978-1-5090-6020-7 (ISBN)
Conference
FUZZ-IEEE 2018, Rio de Janeiro, Brazil, 8-13 July, 2018
Available from: 2018-07-23 Created: 2018-07-23 Last updated: 2018-09-04Bibliographically approved
Palm, R. & Lilienthal, A. (2017). Long distance prediction and short distance control in Human-Robot Systems. In: 2017 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE): . Paper presented at 2017 IEEE International Conference on Fuzzy Systems (FUZZ 2017), Naples, Italy, July 9-12, 2017. Institute of Electrical and Electronics Engineers (IEEE), Article ID 8015396.
Open this publication in new window or tab >>Long distance prediction and short distance control in Human-Robot Systems
2017 (English)In: 2017 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE), Institute of Electrical and Electronics Engineers (IEEE), 2017, article id 8015396Conference paper, Published paper (Refereed)
Abstract [en]

The study of the interaction between autonomous robots and human agents in common working areas is an emerging field of research. Main points thereby are human safety, system stability, performance and optimality of the whole interaction process. Two approaches to deal with human-robot interaction can be distinguished: Long distance prediction which requires the recognition of intentions of other agents, and short distance control which deals with actions and reactions between agents and mutual reactive control of their motions and behaviors. In this context obstacle avoidance plays a prominent role. In this paper long distance prediction is represented by the identification of human intentions to use specific lanes by using fuzzy time clustering of pedestrian tracks. Another issue is the extrapolation of parts of both human and robot trajectories in the presence of scattered/uncertain measurements to guarantee a collision-free robot motion. Short distance control is represented by obstacle avoidance between agents using the method of velocity obstacles and both analytical and fuzzy control methods.

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers (IEEE), 2017
National Category
Robotics
Research subject
Computer Science
Identifiers
urn:nbn:se:oru:diva-64764 (URN)10.1109/FUZZ-IEEE.2017.8015396 (DOI)2-s2.0-85030175947 (Scopus ID)978-1-5090-6034-4 (ISBN)978-1-5090-6035-1 (ISBN)978-1-5090-6033-7 (ISBN)
Conference
2017 IEEE International Conference on Fuzzy Systems (FUZZ 2017), Naples, Italy, July 9-12, 2017
Available from: 2018-02-01 Created: 2018-02-01 Last updated: 2018-02-02Bibliographically approved
Palm, R., Chadalavada, R. & Lilienthal, A. (2016). Fuzzy Modeling and Control for Intention Recognition in Human-Robot Systems. In: Proceedings of the 8th International Joint Conference on Computational Intelligence (IJCCI 2016): . Paper presented at 8th International Conference on Computational Intelligence IJCCI 2016, FCTA, Porto, Portugal, November 9-11, 2016 (pp. 67-74). Setúbal, Portugal: SciTePress, 2
Open this publication in new window or tab >>Fuzzy Modeling and Control for Intention Recognition in Human-Robot Systems
2016 (English)In: Proceedings of the 8th International Joint Conference on Computational Intelligence (IJCCI 2016), Setúbal, Portugal: SciTePress, 2016, Vol. 2, p. 67-74Conference paper, Published paper (Refereed)
Abstract [en]

The recognition of human intentions from trajectories in the framework of human-robot interaction is a challenging field of research. In this paper some control problems of the human-robot interaction and their intentions to compete or cooperate in shared work spaces are addressed and the time schedule of the information flow is discussed. The expected human movements relative to the robot are summarized in a so-called "compass dial" from which fuzzy control rules for the robot's reactions are derived. To avoid collisions between robot and human very early the computation of collision times at predicted human-robot intersections is discussed and a switching controller for collision avoidance is proposed. In the context of the recognition of human intentions to move to certain goals, pedestrian tracks are modeled by fuzzy clustering, lanes preferred by human agents are identified, and the identification of degrees of membership of a pedestrian track to specific lanes are discussed. Computations based on simulated and experimental data show the applicability of the methods presented.

Place, publisher, year, edition, pages
Setúbal, Portugal: SciTePress, 2016
Keywords
Fuzzy control, Fuzzy modeling, Human-Robot interaction, human intentions
National Category
Computer and Information Sciences
Research subject
Computer Science
Identifiers
urn:nbn:se:oru:diva-53710 (URN)10.5220/0006015400670074 (DOI)000393153800005 ()2-s2.0-85006466619 (Scopus ID)978-989-758-201-1 (ISBN)
Conference
8th International Conference on Computational Intelligence IJCCI 2016, FCTA, Porto, Portugal, November 9-11, 2016
Projects
Action and Intention Recognition in Human Interaction with Autonomous Systems
Note

Funding Agency:

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
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, p. 4489-4494Conference 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
Keywords
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: 2018-07-17Bibliographically approved
Palm, R., Chadalavada, R. & Lilienthal, A. (2016). Recognition of Human-Robot Motion Intentions by Trajectory Observation. In: 2016 9th International Conference on Human System Interactions, HSI 2016: Proceedings. Paper presented at The 9th International Conference on Human System Interaction (HSI2016), Portsmouth, UK, July 6-8, 2016 (pp. 229-235). New York: Institute of Electrical and Electronics Engineers (IEEE)
Open this publication in new window or tab >>Recognition of Human-Robot Motion Intentions by Trajectory Observation
2016 (English)In: 2016 9th International Conference on Human System Interactions, HSI 2016: Proceedings, New York: Institute of Electrical and Electronics Engineers (IEEE), 2016, p. 229-235Conference paper, Published paper (Refereed)
Abstract [en]

The intention of humans and autonomous robots to interact in shared spatial areas is a challenging field of research regarding human safety, system stability and performance of the system's behavior. In this paper the intention recognition between human and robot from the control point of view are addressed and the time schedule of the exchanged signals is discussed. After a description of the kinematic and geometric relations between human and robot a so-called 'compass dial' with the relative velocities is presented from which suitable fuzzy control rules are derived. The computation of the collision times at intersections and possible avoidance strategies are further discussed. Computations based on simulated and experimental data show the applicability of the methods presented.

Place, publisher, year, edition, pages
New York: Institute of Electrical and Electronics Engineers (IEEE), 2016
Series
Conference on Human System Interaction
Keywords
Human robot interaction, human intentions, obstacle avoidance, fuzzy rules
National Category
Computer and Information Sciences
Research subject
Computer Science
Identifiers
urn:nbn:se:oru:diva-53700 (URN)10.1109/HSI.2016.7529636 (DOI)000392278000029 ()2-s2.0-84992193870 (Scopus ID)9781509017294 (ISBN)
Conference
The 9th International Conference on Human System Interaction (HSI2016), Portsmouth, UK, July 6-8, 2016
Projects
Action and Intention Recognition in Human Interaction with Autonomous Systems
Note

Funding Agency:

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
Palm, R. & Driankov, D. (2015). Velocity potentials and fuzzy modeling of fluid streamlines for obstacle avoidance of mobile robots. In: 2015 IEEE International Conference on Fuzzy Systems, (FUZZ-IEEE): . Paper presented at 2015 IEEE International Conference on Fuzzy Systems, (FUZZ-IEEE) Istanbul, Turkey, August 2-5, 2015 (pp. 1-8). IEEE Press
Open this publication in new window or tab >>Velocity potentials and fuzzy modeling of fluid streamlines for obstacle avoidance of mobile robots
2015 (English)In: 2015 IEEE International Conference on Fuzzy Systems, (FUZZ-IEEE), IEEE Press, 2015, p. 1-8Conference paper, Published paper (Refereed)
Abstract [en]

The use of the velocity potential of an incompressible fluid is an important and elegant tool for obstacle avoidance of mobile robots. Obstacles are modeled as cylindrical objects - combinations of cylinders can also form super obstacles. Possible trajectories of a vehicle are given by a set of streamlines around the obstacle computed by the velocity potential. Because of the number of streamlines and of data points involved therein, models of sets of streamlines for different sizes of obstacles are created first using dataset models and finally fuzzy models of streamlines. Once an obstacle appears in the sensor cone of the robot the set of streamlines is computed from which that streamline is selected that guarantees a smooth transition from/to the planned trajectory. Collisions with other robots are avoided by a combination of velocity potential and force potential and/or the change of streamlines during operation (lane hopping).

Place, publisher, year, edition, pages
IEEE Press, 2015
Keywords
obstacle avoidance; velocity potential; fuzzy modeling; streamlines
National Category
Robotics
Research subject
Informatics
Identifiers
urn:nbn:se:oru:diva-47940 (URN)10.1109/FUZZ-IEEE.2015.7337800 (DOI)000370288300002 ()978-1-4673-7428-6 (ISBN)
Conference
2015 IEEE International Conference on Fuzzy Systems, (FUZZ-IEEE) Istanbul, Turkey, August 2-5, 2015
Projects
AIR
Available from: 2016-02-04 Created: 2016-02-04 Last updated: 2017-10-17Bibliographically approved
Palm, R. & Driankov, D. (2014). Fluid mechanics for path planning and obstacle avoidance of mobile robots. In: J.Filipe, O. Gusikhin, K.Madani, J. Sasiadek (Ed.), ICINCO 2014 proceedings of the 11th International Conference on Informatics in Control Automation and Robotics: . Paper presented at 11th International Conference on Informatics in Control, Automation and Robotics, Vienna, Austria (pp. 231-238). SciTePress
Open this publication in new window or tab >>Fluid mechanics for path planning and obstacle avoidance of mobile robots
2014 (English)In: ICINCO 2014 proceedings of the 11th International Conference on Informatics in Control Automation and Robotics / [ed] J.Filipe, O. Gusikhin, K.Madani, J. Sasiadek, SciTePress, 2014, p. 231-238Conference paper, Published paper (Refereed)
Abstract [en]

Obstacle avoidance is an important issue for off-line path planning and on-line reaction to unforeseen appearance of obstacles during motion of a non-holonomic mobile robot along apredefined trajectory. Possible trajectories for obstacle avoidance are modeled by the velocity potential using a uniform flow plus a doublet representing a cylindrical obstacle. In the case of an appearance of an obstacle in the sensor cone of the robot a set of streamlines is computed from which a streamline is selected that guarantees a smooth transition from/to the planned trajectory. To avoid collisions with other robots a combination of velocity potential and force potential and/or the change of streamlines during operation (lane hopping) are discussed.

Place, publisher, year, edition, pages
SciTePress, 2014
Keywords
Mobile robots, obstacle avoidance, fluid mechanics, velocity potential
National Category
Engineering and Technology Computer Sciences
Research subject
Computer Science
Identifiers
urn:nbn:se:oru:diva-38966 (URN)978-989-758-040-6 (ISBN)
Conference
11th International Conference on Informatics in Control, Automation and Robotics, Vienna, Austria
Projects
SAUNA - Safe Autonomous Navigation
Funder
Knowledge Foundation
Available from: 2014-11-25 Created: 2014-11-25 Last updated: 2018-01-11Bibliographically approved
Palm, R. & Iliev, B. (2014). Programming-by-Demonstration and Adaptation of Robot Skills by Fuzzy Time Modeling. International Journal of Humanoid Robotics, 11(1), Article ID 1450009.
Open this publication in new window or tab >>Programming-by-Demonstration and Adaptation of Robot Skills by Fuzzy Time Modeling
2014 (English)In: International Journal of Humanoid Robotics, ISSN 0219-8436, Vol. 11, no 1, article id 1450009Article in journal (Refereed) Published
Abstract [en]

Robot skills are motion or grasping primitives from which a complicated robot task consists. Skills can be directly learned and recognized by a technique named programming-bydemonstration. A human operator demonstrates a set of reference skills where his motions are recorded by a data-capturing system and modeled via fuzzy clustering and a Takagi–Sugeno modeling technique. The skill models use time instants as input and operator actions as outputs. In the recognition phase, the robot identi¯es the skill shown by the operator in a novel test demonstration. Finally, using the corresponding reference skill model the robot executes the recognized skill. Skill models can be updated online where drastic di®erences between learned and real world conditions are eliminated using the Broyden update formula. This method was extended for fuzzy models especially for time cluster models.

Place, publisher, year, edition, pages
Singapore: World Scientific, 2014
Keywords
Fuzzy modeling; time clustering; robot skills; programming-by-demonstration
National Category
Engineering and Technology
Research subject
Computer Science
Identifiers
urn:nbn:se:oru:diva-34713 (URN)10.1142/S0219843614500091 (DOI)000334602700007 ()2-s2.0-84898453229 (Scopus ID)
Note

Funding Agencies:

HANDLE project

European Communitys Seventh Framework Programme

Available from: 2014-04-12 Created: 2014-04-12 Last updated: 2017-10-18Bibliographically 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, p. 1378-1379Article 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.

Keywords
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
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