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Palm, Rainer
Publications (10 of 42) Show all publications
Chadalavada, R. T., Andreasson, H., Schindler, M., Palm, R. & Lilienthal, A. J. (2020). Bi-directional navigation intent communication using spatial augmented reality and eye-tracking glasses for improved safety in human-robot interaction. Robotics and Computer-Integrated Manufacturing, 61, Article ID 101830.
Open this publication in new window or tab >>Bi-directional navigation intent communication using spatial augmented reality and eye-tracking glasses for improved safety in human-robot interaction
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2020 (English)In: Robotics and Computer-Integrated Manufacturing, ISSN 0736-5845, E-ISSN 1879-2537, Vol. 61, article id 101830Article in journal (Refereed) Published
Abstract [en]

Safety, legibility and efficiency are essential for autonomous mobile robots that interact with humans. A key factor in this respect is bi-directional communication of navigation intent, which we focus on in this article with a particular view on industrial logistic applications. In the direction robot-to-human, we study how a robot can communicate its navigation intent using Spatial Augmented Reality (SAR) such that humans can intuitively understand the robot's intention and feel safe in the vicinity of robots. We conducted experiments with an autonomous forklift that projects various patterns on the shared floor space to convey its navigation intentions. We analyzed trajectories and eye gaze patterns of humans while interacting with an autonomous forklift and carried out stimulated recall interviews (SRI) in order to identify desirable features for projection of robot intentions. In the direction human-to-robot, we argue that robots in human co-habited environments need human-aware task and motion planning to support safety and efficiency, 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 what can be inferred from the trajectory and head pose of a person. Hence, we propose eye-tracking glasses as safety equipment in industrial environments shared by humans and robots. In this work, we investigate the possibility of human-to-robot implicit intention transference solely from eye gaze data and evaluate how the observed eye gaze patterns of the participants relate to their navigation decisions. We again analyzed trajectories and eye gaze patterns of humans while interacting with an autonomous forklift for clues that could reveal direction intent. 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 gaze for early obstacle avoidance.

Place, publisher, year, edition, pages
Elsevier, 2020
Keywords
Human-robot interaction (HRI), Mobile robots, Intention communication, Eye-tracking, Intention recognition, Spatial augmented reality, Stimulated recall interview, Obstacle avoidance, Safety, Logistics
National Category
Computer Vision and Robotics (Autonomous Systems)
Identifiers
urn:nbn:se:oru:diva-78358 (URN)10.1016/j.rcim.2019.101830 (DOI)000496834800002 ()2-s2.0-85070732550 (Scopus ID)
Note

Funding Agencies:

KKS SIDUS project AIR: "Action and Intention Recognition in Human Interaction with Autonomous Systems"  20140220

H2020 project ILIAD: "Intra-Logistics with Integrated Automatic Deployment: Safe and Scalable Fleets in Shared Spaces"  732737

Available from: 2019-12-03 Created: 2019-12-03 Last updated: 2020-02-06Bibliographically approved
Asl, R. M., Palm, R., Wu, H. & Handroos, H. (2020). Fuzzy-Based Parameter Optimization of Adaptive Unscented Kalman Filter: Methodology and Experimental Validation. IEEE Access, 8, 54887-54904
Open this publication in new window or tab >>Fuzzy-Based Parameter Optimization of Adaptive Unscented Kalman Filter: Methodology and Experimental Validation
2020 (English)In: IEEE Access, E-ISSN 2169-3536, Vol. 8, p. 54887-54904Article in journal (Refereed) Published
Abstract [en]

This study introduces a fuzzy based optimal state estimation approach. The new method is based on two principles: Adaptive Unscented Kalman filter, and Fuzzy Adaptive Grasshopper Optimization Algorithm. The approach is designed for the optimization of an adaptive Unscented Kalman Filter. To find the optimal parameters for the filter, a fuzzy based evolutionary algorithm, named Fuzzy Adaptive Grasshopper Optimization Algorithm, is developed where its efficiency is verified by application to different benchmark functions. The proposed optimal adaptive unscented Kalman filter is applied to two nonlinear systems: a robotic manipulator, and a servo-hydraulic system. Different simulation tests are conducted to verify the performance of the filter. The results of simulations are presented and compared with a previous version of the unscented Kalman filter. For a realistic test, the proposed filter is applied on the practical servo-hydraulic system. Practical results are discussed, and presented results approve the capability of the presented method for practical applications.

Place, publisher, year, edition, pages
IEEE, 2020
Keywords
Kalman filters, Optimization, Nonlinear systems, Estimation, Robots, Evolutionary computation, Adaptive systems, Adaptive unscented Kalman filter, state estimation, fuzzy adaptive grasshopper optimization algorithm (FAGOA), time variant noise, robot manipulator
National Category
Computer Sciences
Identifiers
urn:nbn:se:oru:diva-81338 (URN)10.1109/ACCESS.2020.2979987 (DOI)000524750000018 ()2-s2.0-85082716391 (Scopus ID)
Available from: 2020-04-24 Created: 2020-04-24 Last updated: 2020-04-24Bibliographically approved
Palm, R., Chadalavada, R. T. & Lilienthal, A. (2019). Fuzzy Modeling, Control and Prediction in Human-Robot Systems. In: Juan Julian Merelo, Fernando Melício José M. Cadenas, António Dourado, Kurosh Madani, António Ruano, Joaquim Filipe (Ed.), Computational Intelligence: International Joint Conference, IJCCI2016 Porto, Portugal, November 9–11,2016 Revised Selected Papers (pp. 149-177). Switzerland: Springer Publishing Company
Open this publication in new window or tab >>Fuzzy Modeling, Control and Prediction in Human-Robot Systems
2019 (English)In: Computational Intelligence: International Joint Conference, IJCCI2016 Porto, Portugal, November 9–11,2016 Revised Selected Papers / [ed] Juan Julian Merelo, Fernando Melício José M. Cadenas, António Dourado, Kurosh Madani, António Ruano, Joaquim Filipe, Switzerland: Springer Publishing Company, 2019, p. 149-177Chapter in book (Refereed)
Abstract [en]

A safe and synchronized interaction between human agents and robots in shared areas requires both long distance prediction of their motions and an appropriate control policy for short distance reaction. In this connection recognition of mutual intentions in the prediction phase is crucial to improve the performance of short distance control.We suggest an approach for short distance control inwhich the expected human movements relative to the robot are being summarized in a so-called “compass dial” from which fuzzy control rules for the robot’s reactions are derived. To predict possible collisions between robot and human at the earliest possible time, the travel times to predicted human-robot intersections are calculated and fed into a hybrid controller for collision avoidance. By applying the method of velocity obstacles, the relation between a change in robot’s motion direction and its velocity during an interaction is optimized and a combination with fuzzy expert rules is used for a safe obstacle avoidance. For a prediction of human intentions to move to certain goals pedestrian tracks are modeled by fuzzy clustering, and trajectories of human and robot agents are extrapolated to avoid collisions at intersections. Examples with both simulated and real data show the applicability of the presented methods and the high performance of the results.

Place, publisher, year, edition, pages
Switzerland: Springer Publishing Company, 2019
Series
Studies in Computational Intelligence, ISSN 1860-949X, E-ISSN 1860-9503 ; 792
Keywords
Fuzzy control, Fuzzy modeling, Prediction, Human-robot interaction, Human intentions, Obstacle avoidance, Velocity obstacles
National Category
Computer Sciences
Research subject
Computer Science
Identifiers
urn:nbn:se:oru:diva-79743 (URN)10.1007/978-3-319-99283-9 (DOI)978-3-319-99282-2 (ISBN)978-3-319-99283-9 (ISBN)
Funder
Knowledge Foundation, 20140220
Available from: 2020-02-03 Created: 2020-02-03 Last updated: 2020-02-05Bibliographically approved
Palm, R. & Lilienthal, A. J. (2019). Gaussian Noise and the Intersection Problem in Human-Robot Systems: Analytical and Fuzzy Approach. In: 2019 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE): . Paper presented at IEEE International Conference on Fuzzy Systems (FUZZ-IEEE 2019), New Orleans, USA, June 23 - 26, 2019 (pp. 1-6). IEEE, Article ID 8858796.
Open this publication in new window or tab >>Gaussian Noise and the Intersection Problem in Human-Robot Systems: Analytical and Fuzzy Approach
2019 (English)In: 2019 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE), IEEE, 2019, p. 1-6, article id 8858796Conference paper, Published paper (Refereed)
Abstract [en]

In this paper the intersection problem in humanrobot systems with respect to noisy information is discussed. The interaction between humans and mobile robots in shared areas requires a high level of safety especially at the intersections of trajectories. We discuss the intersection problem with respect to noisy information on the basis of an analytic geometrical model and its TS fuzzy version. The transmission of a 2-dimensional Gaussian noise signal, in particular information on human and robot orientations, through a non-linear static system and its fuzzy version, will be described. We discuss the problem: Given the parameters of the input distributions, find the parameters of the output distributions.

Place, publisher, year, edition, pages
IEEE, 2019
Keywords
Humn Robot Interaction, Human Motion Prediction, Collision Avoidance
National Category
Computer Sciences
Research subject
Computer Science
Identifiers
urn:nbn:se:oru:diva-79734 (URN)10.1109/FUZZ-IEEE.2019.8858796 (DOI)978-1-5386-1729-8 (ISBN)
Conference
IEEE International Conference on Fuzzy Systems (FUZZ-IEEE 2019), New Orleans, USA, June 23 - 26, 2019
Projects
ILIAD
Funder
Knowledge Foundation, 20140220
Available from: 2020-02-03 Created: 2020-02-03 Last updated: 2020-02-14Bibliographically approved
Asl, R. M., Hagh, Y. S., Palm, R. & Handroos, H. (2019). Integral Non-Singular Terminal Sliding Mode Controller for nth-Order Nonlinear Systems. IEEE Access, 7, 102792-102802
Open this publication in new window or tab >>Integral Non-Singular Terminal Sliding Mode Controller for nth-Order Nonlinear Systems
2019 (English)In: IEEE Access, E-ISSN 2169-3536, Vol. 7, p. 102792-102802Article in journal (Refereed) Published
Abstract [en]

In this study, a new integral non-singular terminal sliding mode control method for nonlinear systems is introduced. The proposed controller is designed by defining a new sliding surface with an additional integral part. This new manifold is first introduced into the second-order system and then expanded to nth-order systems. The stability of the control system is demonstrated for both second-order and nth-order systems by using the Lyapunov stability theory. The proposed controller is applied to a robotic manipulator as a case study for second-order systems, and a servo-hydraulic system as a case study for third-order systems. The results are presented and discussed.

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers (IEEE), 2019
Keywords
Integral non-singular terminal sliding mode controller, Lyapunov stability, robotic manipulator, servo-hydraulic system, trajectory tracking
National Category
Computer Sciences
Identifiers
urn:nbn:se:oru:diva-76073 (URN)10.1109/ACCESS.2019.2930798 (DOI)000481688500192 ()
Available from: 2019-09-05 Created: 2019-09-05 Last updated: 2019-09-05Bibliographically approved
Palm, R. & Lilienthal, A. J. (2019). Uncertainty and Fuzzy Modeling in Human-Robot Navigation. In: Proceedings of the 11th International Joint Conference on Computational Intelligence: Volume 1 (FCTA). Paper presented at 11th International Joint Conference on Computational Intelligence - Volume 1 (FCTA), Vienna, Austria, September 17 - 19, 2019 (pp. 296-305). SciTePress
Open this publication in new window or tab >>Uncertainty and Fuzzy Modeling in Human-Robot Navigation
2019 (English)In: Proceedings of the 11th International Joint Conference on Computational Intelligence: Volume 1 (FCTA), SciTePress, 2019, p. 296-305Conference paper, Published paper (Refereed)
Abstract [en]

The interaction between humans and mobile robots in shared areas requires a high level of safety especially at the crossings of the trajectories of humans and robots. We discuss the intersection calculation and its fuzzy version in the context of human-robot navigation with respect to noise information. Based on known parameters of the Gaussian input distributions at the orientations of human and robot the parameters of the output distributions at the intersection are to be found by analytical and fuzzy calculation. Furthermore the inverse task is discussed where the parameters of the output distributions are given and the parameters of the input distributions are searched. For larger standard deviations of the orientation signals we suggest mixed Gaussian models as approximation of nonlinear distributions.

Place, publisher, year, edition, pages
SciTePress, 2019
Keywords
Human-robot Interaction, Navigation, Fuzzy Modeling, Gaussian Noise
National Category
Computer Sciences
Research subject
Computer Science
Identifiers
urn:nbn:se:oru:diva-79741 (URN)10.5220/0008344902960305 (DOI)978-989-758-384-1 (ISBN)
Conference
11th International Joint Conference on Computational Intelligence - Volume 1 (FCTA), Vienna, Austria, September 17 - 19, 2019
Funder
Knowledge Foundation, 20140220
Available from: 2020-02-03 Created: 2020-02-03 Last updated: 2020-02-06Bibliographically approved
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 ; 8
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)000462212700041 ()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: 2019-04-04Bibliographically 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
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