The Department of Industrial Engineering and Management

Ben-Gurion University of the Negev

The Intelligent systems engineering laboratory (ISEL) in the department of Industrial Engineering and Management, at Ben-Gurion University of the Negev, focuses on analysis and engineering of intelligent systems capable of dexterous motion. We develop deterministic and stochastic models for synthesis of robotic motion and for analysis of human motion and study the interaction between perception and action in physical, virtual, and augmented environments. We design and build cyber-physical systems in various application fields (e.g., agriculture, rehabilitation, and the digital factory). 

Agriculture: We are developing advanced robotic precision agricultural systems with sensor fusion and data analysis capabilities, which will enhance production yield along with sustainability. Upper-limb rehabilitation: We are developing robotic and virtual reality-based systems for advancing functional recovery following stroke based on advanced motor control theories. The digital factory: we are developing cyber-physical systems capable of learning and adaptation based on user intent identification, implementing Industrial Internet of Things (IIoT) concepts.

We are looking for excellent undergraduate and graduate students interested in advanced modeling and analysis, machine learning, system engineering, virtual and augmented reality, robotics, and human motor control. 

Lab director: Prof. Sigal Berman

 

Selected research projects

Error Augmentation for Upper Limb Rehabilitation for Stroke Survivors

Stroke is a leading cause of long-term sensorimotor disability with deficits in upper limb function persisting into the chronic stage in a large proportion of stoke survivors. This may partly be due to the limited effectiveness of current upper limb rehabilitation interventions. A stronger focus on training aligned with addressing the underlying causes of the motor control deficits rather than on only behavioral output, may be essential for significantly improving treatment outcomes. Multiple efforts have been initiated for augmenting rehabilitation following stroke with the advent of advanced technology, such as robotics or virtual reality (VR). One of the explored possibilities is based on error augmentation (EA). In EA treatment, subjects are provided with feedback that enhances their motor errors. This is usually done with distorted visual feedback and, using robots, by providing haptic feedback based on motion error. EA has resulted in positive effects for lower limb locomotor training but results for upper limb training are inconclusive. The current project investigates the effects of EA treatment for upper limb rehabilitation in subjects with stroke. We are developing training protocols based on motor control theory to re-mediate underlying movement deficits.

Funding: the Helmsley Charitable Trust through the Agricultural, Biological and Cognitive Robotics Center of Ben-Gurion University of the Negev and BGU Multi-disciplinary brain research.

Perception and action in remote and virtual environments

Telerobotic control and virtual reality (VR) environments share many similarities, e.g., the inherent spatial and temporal separation between perception and action. Moreover, VR is used in many telerobotic systems for locally closing the operator’s control loop facilitating separate operation of the remote and operator sites. Understanding the perception-action mechanisms and their applicability for telerobotic control and virtual environments is expected to facilitate the development of objective measures of system transparency, improved interface designs, along with improved operator training routines. Moreover, both remote and virtual environments, offer a unique platform for examining the mechanisms that underlie perception and action. In reach to grasp motion, a reaching movement is performed in free space, while the goal configuration is constrained by the configuration afforded by the object and functional task. Contact with the object is made at the end of the movement. Object characteristics, e.g., size, weight and texture, determine the finger aperture required for a successful grasp. Unlike grasping, the goal of reaching movements is in free space and the final hand orientation is typically not constrained. During reaching movements, when obstacles are present, movement trajectories are adjusted in order to avoid a potential contact with the obstacle. In the current project, we examine the influence of the interface, object and obstacle size, transmission delays, and viewing conditions, on motion in virtual and telerobotic environments. 

Related publications:

O. Afgin, N. Sagi, I. Nisky, T. Ganel, S. Berman, 2017, Visuomotor resolution in telerobotic grasping with transmission delays, Frontiers in Robotics and AI-Bionics and Biomimetics, https://doi.org/10.3389/frobt.2017.00054 .

 

A. OzanaS, S. BermanC, and T. GanelPI, 2018. Grasping trajectories in a virtual environment adhere to Weber’s law. Experimental Brain Research, 236(6):1775–1787 .

 

A. Milstein, T. Ganel, S. Berman, I. Nisky, 2018.  Transparency of grasping via a robot-assisted minimally invasive surgery system. IEEE Trans Human Machine Systems, 48(4): 349 - 358. 

Industrial Internet of Things (IIOT) communication integrated in the telerobotic system

Funding: the Helmsley Charitable Trust through the Agricultural, Biological and Cognitive Robotics Center of Ben-Gurion University of the Negev.

Robotic Medjool-date thinning 

Fruitlet thinning is an important task of Mejdool-date cultivation. Precise and scrutinized thinning is an essential stage toward attaining high quality yields. Currently, thinning is a labor-intensive process and automation of this process is essential to enable fruitlet thinning of larger plots with reduced man power. We are part of a multi-disciplinary team working together on the development of  robot for Medjool-date thinning. We are in charge of motion planning and fruitlet cluster identification. We are working with dynamic motion primitives, learning motion parameters using deep learning and kernel estimation methods. We are applying stochastic models for data generation. Using Bayesian methods for learning model parameters.  

Medjool cluster recognition

Funding: the Israeli Ministry of Agriculture & Rural Development and the Israeli plant council.

AVR4Nano- Acoustic-Visual mobile Robotic manipulator for application of Nanostructures in agriculture

A major challenge in agricultural crop production, is containing and treating biotic and abiotic stresses in order to prevent epidemics, and to avoid yield losses. To significantly improve the capabilities of active compound application we are developing an innovative robotic solution for application of nanostructures in agriculture. Such a system offers a groundbreaking new direction in precision agriculture facilitating efficient application of nanostructures which encapsulate active compounds to their target sites on the plant. In a previous project we developed a robot-based system for disease identification in pepper plants. Automatic disease identification and eradication are expected to significantly improve yield, profitability, and sustainability.  

Related publications:

N. Schor, A. Bechar, T. Ignat, A. Dombrovsky, Y. Elad and S. Berman, 2016, Robotic disease detection in greenhouses: combined detection of Powdery Mildew and Tomato Spotted Wilt Virus, IEEE Robotics and Automation Letters (RA-L) (and IEEE International Conference on Robotics and Automation - ICRA)).

 

N. Schor, S. Berman, A. Dombrovsky, Y. Elad, T. Ignat and A. Bechar, 2016. Development of a robotic detection system for greenhouse pepper plant diseases, Precision Agriculture, 18)3(:394–409.

Funding: the Israeli Ministry of Science and Technology (MOST).

ENHANCE - Enhancing brain plasticity for sensorimotor recovery in spastic hemiparesis

Spasticity is characterized by a velocity-dependent increase in tonic stretch reflexes in muscles at rest and during movement. In subjects with stroke, spatial threshold control of muscle reflexes is diminished. The reduced capability leads to abnormal muscle activation patterns i.e., excessive co-activation, as well as spasticity and weakness within well-defined spatial (angular) zones. The ENHANCE project is tri-national (Canada, India, Israel) effort  harnessing advanced technologies such as virtual reality and Transcranial direct current stimulation (tDCS) for motor rehabilitation flowing stroke. Our team is in charge of analyzing the kinamtic data collected as part of the project. We are using advanced stochastic model for assessing the effects of spasticity on motion kinematics.

Related publications:

M. F. Levin, M. C. Baniña, S. Frenkel-Toledo, S. Berman, N. Soroker, J. M Solomon, D. G. Liebermann, 2018, Personalized upper limb training combined with anodal-tDCS for sensorimotor recovery in spastic hemiparesis: study protocol for a randomized controlled trial, Trials, 19:7, https://doi.org/10.1186/s13063-017-2377-6 .

 

I. Davitowitz, Y. Parmet, M. C. Baniña, S. Frenkel-Toledo, N. Soroker, J. M. Solomon, D. G. Liebermann, M. F. Levin, S. Berman, 2019. Effects of spasticity on upper limb movement in patients with stroke using stochastic spatiotemporal modeling, Neurorehabilitation and Neural Repair, 33(2): 141–152. [Link]

Funding: the Israel Science Foundation  (ISF) , the Azrieli foundation, the Canadian Institutes of Health Research (CIHR) and the International Development Research Center (IDRC)

CIM NEGEV 2001 operation

Inferring human intent in remote-control scenarios

The ability of inferring human intent can be instrumental in many human-robot interaction scenarios. Inferred intentions can be at both tactical and strategic levels. As remote operation becomes more prevalent, complex new interaction scenarios are emerging, e.g., a human remotely controlling a robot which interacts with another robot. The addition of a remotely controlled robot present further challenges to the already challenging task of inferring human intent. We have built in simulation and with hardware a robotic table soccer game where two robots facing each other hit a ball placed within a game court to form a test-bed for idenfitying human intent in remote scenarios. One robot is controlled autonomously using machine vision and learning algorithms, and the other is controlled by a remote human operator. 

Funding: the Helmsley Charitable Trust through the Agricultural, Biological and Cognitive Robotics Initiative and the Paul Ivanier Center for Production Management at Ben-Gurion University of the Negev

 

Selected journal publications

H. Stern, M. Shmueli and S. Berman, 2013. Most discriminating segment - longest common subsequence (MDSLCS) algorithm for dynamic hand gesture classification, Pattern Recognition Letters (Special issue on 'Smart Approaches for Human Action Recognition’), 34: 1980-1989.

 

T. Merdler, D.G. Liebermann, M. F. Levin and S. Berman, 2013. Arm-plane representation of shoulder compensation during pointing movements in patients with stroke, Journal of Electromyography & Kinesiology, 23: 938-947.

 

S. Berman, D.G. Liebermann and J. McIntyre, 2014. Constrained motion control on a hemispherical surface - path planning, Journal of Neurophysiology, 111(5): 954-68.

 

O. Mendels, H. Stern and S. Berman, 2014. User identification for home entertainment based on free-air hand motion signatures, IEEE Transactions on Systems Man and Cybernetics: Systems, 44(11):1461-1473.

 

D. Eizicovits and S. Berman, 2014. Efficient sensory-grounded grasp pose quality mapping for gripper design and online grasp planning, Journal of Robotics and Autonomous Systems, 62(8): 1208-1219 .

 

S. Haar, S. Berman, M. Behrmann and I. Dinstein, 2014. Anatomical abnormalities in autism?, Cerebral Cortex, October 2014, 1-13. (62 citations; IF: 8.665; Neuroscience: 16/252, Q1)

 

H. Zhong, S.Y. Nof and S. Berman, 2015. Asynchronous cooperation requirement planning with reconfigurable end-effectors, Robotics and Computer Integrated Manufacturing, 34:95-104.

 

G. Naveh, L. Fink, A. Even and S. Berman, 2015, Information technology education in a digital factory learning environment, Intelligent Automation and Soft Computing (Autosoft), 21(4): 659-672.

 

O. Raphaeli, S. Berman and L. Fink, 2015, E-business value creation from a resource-based perspective: a review of the last decade of empirical research, Foundations and Trends in Information Systems, 1(1):1-68.

 

C.W. Bac, T. Roorda, R. Reshef, S. Berman, J. Hemming, E.J. van Henten, 2015, Analysis of a motion planning problem for sweet-pepper harvesting in a dense obstacle environment, Biosystems Engineering, 145, 86:97.

 

M.F. Levin, D.G. LiebermannC, Y. ParmetC and S. BermanPI, 2015, Compensatory vs non-compensatory shoulder movements used for reaching in stroke, Neurorehabilitation and Neural Repair, 30(7):635-46.

 

D. Eizicovits, B. Van Tuijl, S. Berman and Y. Edan, 2016, Integration of perception capabilities in gripper design using graspability maps, Biosystems Engineering, 146:98-113.

 

N. Schor, A. Bechar, T. Ignat, A. Dombrovsky, Y. Elad and S. Berman, 2016, Robotic disease detection in greenhouses: combined detection of Powdery Mildew and Tomato Spotted Wilt Virus, IEEE Robotics and Automation Letters (RA-L) (and IEEE International Conference on Robotics and Automation - ICRA)).

 

N. Schor, S. Berman, A. Dombrovsky, Y. Elad, T. Ignat and A. Bechar, 2016. Development of a robotic detection system for greenhouse pepper plant diseases, Precision Agriculture, 18)3(:394–409.

 

O. Afgin, N. Sagi, I. Nisky, T. Ganel, S. Berman, 2017, Visuomotor resolution in telerobotic grasping with transmission delays, Frontiers in Robotics and AI-Bionics and Biomimetics, https://doi.org/10.3389/frobt.2017.00054 .

 

M. F. Levin, M. C. Baniña, S. Frenkel-Toledo, S. Berman, N. Soroker, J. M Solomon, D. G. Liebermann, 2018, Personalized upper limb training combined with anodal-tDCS for sensorimotor recovery in spastic hemiparesis: study protocol for a randomized controlled trial, Trials, 19:7, https://doi.org/10.1186/s13063-017-2377-6 .

 

A. OzanaS, S. BermanC, and T. GanelPI, 2018. Grasping trajectories in a virtual environment adhere to Weber’s law. Experimental Brain Research, 236(6):1775–1787 .

 

A. Milstein, T. Ganel, S. Berman, I. Nisky, 2018.  Transparency of grasping via a robot-assisted minimally invasive surgery system. IEEE Trans Human Machine Systems, 48(4): 349 - 358. 

I. Davitowitz, Y. Parmet, M. C. Baniña, S. Frenkel-Toledo, N. Soroker, J. M. Solomon, D. G. Liebermann, M. F. Levin, S. Berman, 2019. Effects of spasticity on upper limb movement in patients with stroke using stochastic spatiotemporal modeling, Neurorehabilitation and Neural Repair, 33(2): 141–152. [Link]

Selected conference publications

N. Schor, S. Berman, A. Dombrovsky, Y. Elad, T. Ignat and A. Bechar, 2015. A robotic pepper greenhouse diseases monitoring system, 10th ECPA - European Conference on Precision Agriculture, 12-16 July, Volcani Centre, Israel.

A. Kumar Singh, S. Berman, I. Nisky, 2018, Stochastic Optimal Control for Modeling Reaching Movements in the Presence of Obstacles: Theory and Simulation, 7th IEEE RAS/EMBS International Conference on Biomedical Robotics and Biomechatronics (BioRob 2018), 26-29 August, Enschede, Netherlands.

Undergraduate

364-1-3091 Simulation

Fall 2018

Dynamic Monte-carlo simulation, theory and practice. 

Syllabus (in Hebrew)

364-1-3101 Advanced simulation modeling and analysis

Spring 2019

Modeling, design and analysis of cyber-physical systems. 

Syllabus (in Hebrew)

Graduate

364-2-5421 Intelligent automation systems

Fall 2018

Foundations of intelligent system modeling and design.

Course project: robotic table soccer 

Syllabus (in Hebrew)

2015 project - Autonomous transportation [project description]

2016 project - Plant disease detection (turn a leaf for detecting Powdery Mildew)

2019 project - Robot soccer (Unity simulation by Lily Sror and Ben Rachmut)

MEN4810D_GEN6999GE_SP2020R3_Special Research and Project

Merrimack College, Fall 2020

Mobile robotic manipulators.

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Principal investigator

Sigal Berman 

Associate professor, Industrial Engineering and Management

Office: room 247, building 16, Marcus campus

Phone: 972-8-6479785

Email: sigalbe[at]bgu.ac.il

Research interests: robotics, human motor control, stroke rehabilitation 

Google scholar citations

Students

Hadar Lackritz

MsC student, Industrial Engineering and Management

Office: room -126, building 16, Marcus campus

Email: hadarlac[at]post.bgu.ac.il

 

Project: ENHANCE - Enhancing brain plasticity for sensorimotor recovery in spastic hemiparesis

Or Bar-Shira

MsC student, Industrial Engineering and Management

Office: room -121, building 16, Marcus campus

Email: orrb[at]post.bgu.ac.il

 

Project: Robotic Mejdool date thinning

Tal Shoshan

MsC student, Industrial Engineering and Management

Office: room -121, building 16, Marcus campus

Email: shaubit[at]post.bgu.ac.il

 

Project: Robotic Mejdool date thinning

Alumni

Danny Eizicovits 

MSc Thesis: Examination of constrained motion on a hemispherical surface, Industrial Engineering, 2010

Phd Thesis: Graspability maps: representation, generation and integration in both gripper design and path planning, Industrial Engineering, 2014

Currently: CTO, The Decade Group – Young Engineers Ltd.

Specializes in robotics, embedded programming, industrialization and mass production of electronic toys. 

Phone: 972-528-379-416

Email: danny[at]algobrix.com

Roi Reshef

MSc Thesis: Planning Reach-to-Grasp Motions for a Robotic Arm using Rapid-exploring Random Trees, 2014

Currently: Leading a team of algorithm engineers and researchers that does planning and decision making for GM’s autonomous driving project.
Specializes: in robotics, planning, deep reinforcement learning, software engineering

Email: roireshef[at]hotmail.com

Rotem Duani

MSc Thesis: Bayesian Estimation of Spatial Configuration Distribution, 2017

Currently: Data Scientist at Moovit

Specializes: transportation, statistics and Machine learning

Email: rotemduani40@gmail.com

Nir Sagi

MSc Thesis: Assessing transparency of a gesture-based interface for programming by demonstration, 2016

Currently: Product manager at the Innovation group, Siemens PLM.

Specializes in graphic solutions (mainly AR & web based tools) for industrial use-cases

Phone: +972-50-7482981

Email: nir.sagi@siemens.com \ nirsagi10@gmail.com

Omri Afgin

MSc Thesis: Perception in bilateral telerobotics, 2016

Currently: Data Scientist at Bank Hapoalim, Innovation Division. 

Specializes in Machine Learning, Big Data Analytics and Statistics.

Email: omri17@gmail.com

 

News

24.2.2019 - Papers by Or Bar-Shira, Tal Shoshan, and Lily Sror accepted for oral presentation at the Israeli Industrial Engineering Conference. See you there April 1. 

20.3.2019 - Orr Bar-Shira's paper accepted for oral presentation at the CIOSTA & CIGR Conference is Rhodes. 

O. Bar-Shira, Y. Cohen, T. Shaubi, A. Sadowky, Y. Cohen, A. Bechar, S. Berman, 2019. Learning motion parameters for a Mejdool-date thinning robot, XXXVIII CIOSTA & CIGR Section V Conference, Rhodes, Greece, June 24-26.

23.3.2019 - Hadar Lackritz will be presenting a poster at the Karniel Computational Motor Control Workshop (KCMCW), Monday March 25, 13:30-14:30 (Senate Hall) - come and visit.  

H. Lackritz, Y. Parmet, S. Frenkel-Toledo, M. C. Baniña, N. Soroker, J. M. Solomon, D. G. Liebermann, M. F. Levin., S. Berman, 2019. Stochastic motion modeling, implemented for measuring the effects of spasticity on kinematics, Karniel Computational Motor Control Workshop (KCMCW), Beer-Sheva, March 24-25.

27.3.2019 - Data collection day in Almog (Medjool date farm), testing the perception system engineered by Inbar Ben-David (Volcani) and Tal Shoshan. Thanks all for great support (Yuval, Shmilo, Rafi, Dekel, Moshe, Yael, and Avital). Coming soon - data collection in Yotveta.

01.4.2019 - Israeli Industrial Engineering conference (IIEM). Great presentations by Or Bar-Shira, Tal Shoshan, and Lily Sror.

04.4.2019 - Two international presentations underway - 

Hadar Lackritz's poster accepted for presentation at the Progress in Motor Control conference in Amsterdam: Hadar Lackritz, Silvi Frenkel-Toledo, Melanie C. Baniña, Nachum Soroker, John M. Solomon, Dario G. Liebermann, Mindy F. Levin, Sigal Berman, Quantifying the effects of spasticity on reaching movement patterns using stochastic spatiotemporal modeling. 

Lily Sror's poster accepted for presentation in the International conference on Virtual Rehabilitation in Tel-Aviv: L. Sror, I. Treger, M. Vered, S. Levy-Tzedek, M. F. Levin, S. Berman, 2019. A virtual reality-based training system for error-augmented treatment in patients with stroke.

14.4.2019 - Beautiful pictures gathered in Southern Arava R&D center (down south near Yotveta). Great work by Tal Shoshan, Inbar Ben-David (Volcani). Thanks all for great support (Yuval, Avi, Yael, and Avital).

13.6.2019 - Tal Shoshan's project featured in the Engineering science faculty site, promoting the upcoming project day (20.6). Good luck to Tal and all IEM soon-to-be graduates with their presentations.   

Principal investigator

Sigal Berman 

Associate professor, Industrial Engineering and Management

Office: room 247, building 16, Marcus campus

Phone: 972-8-6479785

Email: sigalbe[at]bgu.ac.il

Research interests: robotics, human motor control, stroke rehabilitation 

Google scholar citations

Students

Omer Dadnon

MsC student, Industrial Engineering and Management

Office: room -126, building 16, Marcus campus

Email: omerdad[at]post.bgu.ac.il

 

Project: Learning robotic motion for Nano particle grape spraying

Shir Ben-David

MsC student, Industrial Engineering and Management

Office: room -121, building 16, Marcus campus

Email: bendshir[at]post.bgu.ac.il

 

Project: Intelligent scheduling of robotic actions for deformable objects

Shahar Agami

MsC student, Industrial Engineering and Management

Office: room -126, building 16, Marcus campus

Email: agami[at]post.bgu.ac.il

 

Project: Error-augmentation for upper limb rehabilitation for stroke survivors 

Tal Shoshan

MsC student, Industrial Engineering and Management

Office: room -121, building 16, Marcus campus

Email: shaubit[at]post.bgu.ac.il

 

Project: Robotic Mejdool date thinning

Alumni

Danny Eizicovits 

MSc Thesis: Examination of constrained motion on a hemispherical surface, Industrial Engineering, 2010

Phd Thesis: Graspability maps: representation, generation and integration in both gripper design and path planning, Industrial Engineering, 2014

Currently: CTO, The Decade Group – Young Engineers Ltd.

Specializes in robotics, embedded programming, industrialization and mass production of electronic toys. 

Phone: 972-528-379-416

Email: danny[at]algobrix.com

Omri Mendels

MSc Thesis: Biometric identification by hand motion signature, 2011 (Co-advisor: Helman Stern)

Currently: Senior Data Scientist at Microsoft. 

Specializes in machine learning and human computer interaction.

Roi Reshef

MSc Thesis: Planning Reach-to-Grasp Motions for a Robotic Arm using Rapid-exploring Random Trees, 2014

Currently: Leading a team of algorithm engineers and researchers that does planning and decision making for GM’s autonomous driving project.
Specializes: in robotics, planning, deep reinforcement learning, software engineering

Email: roireshef[at]hotmail.com

Noa Schor

MSc Thesis: A robotic system for diseases detection of greenhouse peppers, 2015

Currently: data scientist at Bank Leumi, Big Data division. 

Specializes in in machine learning and big data applications as well as statistical analysis.

Nir Sagi

MSc Thesis: Assessing transparency of a gesture-based interface for programming by demonstration, 2016

Currently: Product manager at the Innovation group, Siemens PLM.

Specializes in graphic solutions (mainly AR & web based tools) for industrial use-cases

Phone: +972-50-7482981

Email: nir.sagi[at]siemens.com \ nirsagi10[at]gmail.com

Omri Afgin

MSc Thesis: Perception in bilateral telerobotics, 2016

Currently: Data Scientist at Bank Hapoalim, Innovation Division. 

Specializes in Machine Learning, Big Data Analytics and Statistics.

Email: omri17[at]gmail.com

Rotem Duani

MSc Thesis: Bayesian Estimation of Spatial Configuration Distribution, 2017

Currently: Data Scientist at Moovit

Specializes: transportation, statistics and Machine learning

Email: rotemduani40[at]gmail.com

Isgav Davidowitz 

MSc Thesis: Relationship Between Spasticity and Upper-Limb Movement Disorders in Individuals With Subacute Stroke Using Stochastic Spatiotemporal Modeling, 2017

Currently: Business Analyst at Facebook, working with Health-Tech startups on data driven growth

Specializes: Health-tech, Statistics, Machine Learning, Marketing technology

Email: isgav1[at]gmail.com / isgav[at]fb.com

Hadar Lackritz

MsC thesis: Using Hellinger’s distance for quantifying the effects of spasticity following stroke on voluntary motor control, 2019

Or Bar-Shira

MsC thesis, Learning motion primitive parameters for a Medjool date thinning robot, 2019

Currently: PhD student in the Faculty of Mathematics and Computer Science, Weizmann institute of Science

Lily Sror

MsC thesis: A virtual reality-based training system for error-augmented rehabilitation treatment in patients with stroke, 2019

Tal Merdler, MSc., Objective measures in rehabilitation, Industrial Engineering, BGU, 2011

Eti Almog,  MSc., Comparison of segmentation methods and hand tracking optimization, 2011

Kiril Smilansky, MSc., Classification of compound hand gestures, 2012 (Co-advisor: Helman Stern)

Shani Talmor, MSc., Interfaces for hand gesture browsing systems, 2012

Maayan Yaacobovich, MSc.,Examination of human grasp motion during selective harvesting, 2012

Merav Shmueli, MSc., Longest common subsequence classifiers for hand gesture recognition, 2012 (Co-advisor: Helman Stern)

Peer Shoval, MSc., Automatic guided vehicle dispatching, 2012

Anat Hershkovitz Cohen, MSc., Reach-to-grasp motion using dynamic movement primitives, 2014

Post-doctoral fellows

Dr. Darya Frolova,  Gesture recognition, 2010 - 2011

Dr. Gali Naveh, Collaborative manufacturing network for competitive advantage, 2011 – 2013 (Co-host Lior Fink)

Dr. Orit Raphaeli, Collaborative manufacturing network for competitive advantage, 2012 – 2014 (Co-host Lior Fink)

Dr. Arun Kumar Singh, Human motion prediction and analysis for shared and transparent control, BGU, 2014 – 2016 (Co-host Ilana Nisky)

 

Contact

The Intelligent Systems Engineering Lab (ISEL)

Room -126, building 16

The department of Industrial Engineering and Management (IEM)

Ben-Gurion University of the Negev

email: sigalbe[at]bgu.ac.il

Tel: 972-8-6479785