Come meet us at Ro-Man 2017, where Dr, Vardit Sarne-Fleischmann and Shanee Honig will present our work on Gesture vocabulary for a person following robot.
Abstract— Robots that are designed to support people in different tasks at home and in public areas need to be able to recognize user’s intentions and operate accordingly. To date, research has been mostly concentrated on developing the technological capabilities of the robot and the mechanism of recognition. Still, little is known about navigational commands that could be intuitively communicated by people in order control a robot’s movement. A two-part exploratory study was conducted in order to evaluate how people naturally guide the motion of a robot and whether an existing gesture vocabulary used for human-human communication can be applied to human-robot interaction. Fourteen participants were first asked to demonstrate ten different navigational commands while interacting with a Pioneer robot using a WoZ technique. In the second part of the study participants were asked to identify eight predefined commands from the U.S. Army vocabulary. Results show that simple commands yielded higher consistency among participants regarding the commands they demonstrated. Also, voice commands were more frequent than using gestures, though a combination of both was sometimes more dominant for certain commands. In the second part, an inconsistency of identification rates for opposite commands was observed. The results of this study could serve as a baseline for future developed commands vocabulary promoting a more natural and intuitive human-robot interaction style.
We are excited to present our studies in the 10th University Transportation Centers Spotlight Conference on Pedestrian and Bicycle Safety to be held December 1-2 ,2016 in the Keck Center, Washington DC.
Here is a link to a short description of the BGU pedestrian laboratory.pedestrian-lab-brochure and to a short brief about the work we are presenting (Child Pedestrians’ perceived risk of the crossing place).
Close Target Reconnaissance: A Field Evaluation of Dismounted Soldiers Utilizing Video Feed From an Unmanned Ground Vehicle in Patrol Missions
Oron-Gilad and Parmet (2016) in the Journal of Cognitive Engineering and Decision Making.
- How is the decision cycle of dismounted soldiers affected by the use of a display device displaying video feed from an unmanned ground vehicle in a patrol mission?
- Via a handheld monocular display, participants received a route map and sensor imagery from the vehicle that was ~20–50 m ahead.
- Twenty-two male participants were divided into two groups, with or without the sensor imagery. Each participant navigated for 2 km in a MOUT training facility, while encountering civilians, moving and stationary suspects, and improvised explosive devices.
- Boyd’s OODA loop (observe–orient–decide–act) framework was used to examine
- The experimental group was slower to respond to threats and to orient. They also reported higher workload, more difficulties in allocating their attention to their environment, and more frustration.
- The breakdown of performance metrics into the OODA loop components revealed the major difficulties in the decision-making process and highlighted the need for new roles in combat-team setups and for additional training when unmanned vehicle sensor imagery is introduced.
•• The use of a handheld monocular device for intelligence gathering of information from a UGV affected participants’ ability to detect events with their own eyes.
•• Soldiers were aware of the toll that display devices had on their operational mission, yet it continuously attracted their attention.
•• Soldiers must gain understanding of the capabilities and limitations of the unmanned vehicle and its sensor video; they should be able to control the pace of its progress.
•• Team setups, where only limited designated roles attend to the sensor video and more than one individual attends to the immediate environment, may be a better setup for utilization of the technology.
SOCRATES see project recruitment-poster
With Prof. Yael Edan, we are looking for a Ph.D. student in Human-Robot Interaction Design. The research topic will be: Interaction design for varying levels of automation
Ben-Gurion University is seeking outstanding candidates for a PhD student position in Interaction design for varying levels of automation, at the Department of Industrial Engineering and Management. BGU is an internationally recognized research university that attracts outstanding faculty and researchers from around the world with over 19,000 students. The Industrial Engineering and Management Dept. at BGU includes multidisciplinary faculty with expertise in operations research, applied statistics, intelligent systems, human factors engineering, and information systems. Advanced innovative multidisciplinary robotics research at BGU is conducted under the auspices of the ABC Robotics Initiative.
The recruitment is done as part of SOCRATES (SOcial Cognitive Robotic Agents in The European Society), a new Marie Skłodowska-Curie European Training Network (ETN) comprising of 7 universities/research institutes: Umeå University and Örebro University in Sweden, Universität Hamburg and Fraunhofer IPA, Stuttgart in Germany, CSIC Barcelona in Spain, University West of England, and Ben-Gurion University of the Negev in Israel. Additional non-academic partners are: Pal Robotics, Adele Robots, Alfred Nobel Science Park, Urquhart-Dykes & Lord LLP, Center for Digital Innovation, UMINOVA, Asea Brown Boveri, S.A, and Fundació ACE.
In total 15 Early Stage Researchers (ESRs) will be recruited as PhD students for research on various aspects of social robotics aiming at eldercare. The wide range of projects covers a spectrum from technical design of hardware and interaction methodology, to personalization, user studies, and robot ethics. The researchers will receive training in both academic and entrepreneurial spirit and expertise, well suited for a career in both academy and industry. The training includes a research project, courses, seminars, and workshops. An overview of all available positions can be found at www.socrates-project.eu.
This Research project: Within the realm of assistive robotics for the elderly, the Ph.D. student will aim to develop advanced human-robot interfaces and means of interaction for dynamically changing situations. The focus is on means to improve coordination between users and their robots, and allow the user and the robot to operate as a team with varying levels of control and autonomy, dependent on the context and tasks, in particular in robot learning scenarios. The user involvement and hence the Interaction Quality will vary as a result of the learning progress. This is particularly important to consider when the robot interacts with older adults who have difficulties in identifying changes in the robot’s behavior.
The student will visit Örebro University and the Ängen test facility in Sweden to record and analyze user acceptance for different interface and interaction designs and modalities. Specific experiments will be designed so as to simulate the different types of feedback and changing levels of interaction. These will be implemented on robots in different use-case scenarios with older adults and for different modalities and means of interaction. The research will also include two secondments; one to Bristol Robotics Labs, UK to investigate the relation between adaptive safety control and the human-robot interface design, and one industrial secondment to ADELE Robots, to investigate practical case studies.
About the position: The successful applicant will receive a competitive salary for a period of three years of full time research, provided that the expected study and research results are achieved. No teaching is expected. The salary will be based on the standard Marie Skłodowska-Curie Early-Stage Researcher living and mobility allowances. Expected starting date is 1st of April 2017.
Admission requirements:The applicants must have completed their MSc or MA thesis in Engineering, Computer Sciences, Psychology, or Cognitive science. The applicant must be skilled in both oral and written communication in English, be able to work independently as well as in collaboration with others. We are looking for candidates with strong technical and programming skills. Experience in robotics, human factors, machine learning and statistics are merits. Candidates should have interest in studying human-robot interaction (although should not necessarily have background in such topics) and be passionate about learning and developing knowledge in a novel and exciting area.
Once approved by BGU’s SOCRATES graduate committee the student must be accepted to BGU’s Kreitman graduate school (http://in.bgu.ac.il/en/kreitman_school/Pages/admission.aspx) and obtain a visa and working permit according to the Israeli Ministry of Interior requirements. The candidate must submit a research proposal and go through a Qualification Exam within one year of studies on his/her research proposal.
To promote mobility, the following rule applies: at the time of recruitment, the applicants must not have resided or carried out their main activity in Israel for more than 12 months during the last 3 years. Compulsory national service, work in international organizations, and short stays such as holidays are not taken into account. The applicants must not, at the time of recruitment, have spent more than 4 years doing research, and must not have been awarded a doctoral degree.
Application – a complete application should contain the following documents:
- A cover letter including a description of your research interests, your reasons to apply for the position, and your contact information.
- A curriculum vitae.
- Copies of degree certificates, including documentation of completed academic courses and obtained grades.
- Copy of completed MSc or MA thesis and other original research publications.
- Contact information for three persons willing to act as references (including your thesis advisor).
- Documentation of programming skills and software development experience.
Applications must be submitted electronically to the following email by November 30, 2016.
Applications will be accepted until the position is filled.
For general information about the SOCRATES project, please contact: Prof. Thomas Hellström – firstname.lastname@example.org
Yisrael Parmet, Lee Shoham and Tal Oron-Gilad
Presentation at the ICTTP 2016.
link to presentation: How full vehicle automation affects…
DESCRIPTION: The purpose of this study was to examine the effects of full vehicle automation on performance and behavior, specifically the transition from a fully automated mode to manual driving, under the influence of alcohol and without it. Previous studies have revealed a deterioration in driving performance while transitioning from an automated mode to manual driving and further suggested that automated driving may result in a degraded situation awareness. It was therefore hypothesized that the performance of secondary driving related tasks would deteriorate during the automated phase, while performance of secondary non-driving related tasks would improve, in comparison to manual driving. It was further hypothesized that the transition from automated to manual driving would damage driving performance and that alcohol, while affecting performance of all driving conditions, would affect the manual phase following the automated phase to a greater extent. Method. A fixed base driving simulator was used. The design contained a first manual phase, an automated phase and another manual phase, under the influence of BAC 0.05% alcohol and without it. The study involved 16 participants. Two type of secondary tasks were introduced to the participants, driving and non-driving related tasks and the precision (% of success) and response time (RT) were measured. Driving quality indices such as speed and lane position were measures along the drive as well. Results. In the nondriving related secondary task we found significant differences in the response time only, the response time under the placebo condition were on average 15% higher than the response time under the alcohol condition. In the driving related secondary task we found significant difference in both measures, the participants on average were 5% more accurate and 13% faster while they drove manually. The results of the driving quality indices indicate a deterioration in precision of driving related secondary tasks, and a decrease in driving velocity after an automated phase, the latter being moderated by alcohol, which causes an increase in driving velocity. Conclusion. As hypothesized the performance of secondary driving related tasks deteriorated during the automated phase but contrary to our hypothesis, the automation had no influence on the performance of the non-driving secondary task. Opposing to our hypothesis, we found no evidence that alcohol deteriorates the drivers’ performance in the two types of secondary tasks. The last results might be due to the low level of alcohol that was used in the experiment. As expected we found that driving quality decreases after automated phase and while performing secondary tasks.
Co-authored with Guy Cohen-Lazry, to appear in Technology in Society.
Is staying out of bomb-shelters a human-automation interaction issue?http://dx.doi.org/10.1016/j.techsoc.2016.08.002
“Iron-Dome” is an anti-rocket air defense system placed around major urban areas of Israel. It was created to provide citizens with greater deal of protection against hostile rocket attacks. A study was conducted to examine whether civilians’ experience with the “Iron-Dome” system affects people’s perceived reliability of it, their trust in it, and their complacency to hostile rocket alerts. During the 2014 Israel-Gaza conflict (operation “Protective Edge”), an online questionnaire was used to measure civilian respondents’ perceptions and actions. Results indicated that people living in geographical areas who had more experience with rocket attacks and thereby with the “Iron-Dome” system, perceived it as less reliable, had lower trust in it, and were less complacent. These results show that people’s interaction with the “Iron-Dome” corresponds to the common prediction of theoretical models of human-automation interaction. This understanding may assist in planning of implementation programs and guidance of civilians for other mass protection systems in the future.
Key words: Iron-Dome, Complacency, Trust in automation, Experience, Rocket defense system.
Can traffic violations be traced to gender-role, sensation seeking, demographics and driving exposure?
Background: Traffic safety is often expressed as the ‘inverse of accidents’. However, it is
more than the mere absence of accidents. Past studies often looked for associations
between accidents and self-reports like the Driver Behaviour Questionnaire
(DBQ; Reason, Manstead, Stradling, Baxter, & Campbell, 1990). The focus in this study
changed from counting accidents to quantifying unsafe acts as violations. The objective
was to show that drivers’ specific violations can be traced to personal characteristics such
as sensation seeking (SSS-V; Zuckerman, 1994), gender role (BSRI; Bem sex role inventory,
Bem, 1974), demographics, and driving exposure.
Method: A web-based questionnaire was distributed, integrating several known questionnaires.
Five hundred and twenty-seven questionnaires were completed and analyzed.
Results: Sensation seeking, gender role, experience, and age predicted respondents’ score
on the DBQ, as well as the interaction of sensation seeking with gender and gender role.
Gender role was a more valid predictor of driver behavior than gender.
Conclusions: The effect of gender role on drivers’ self-reported violation tendency is the
most interesting and the most intriguing finding of this survey and indicates the need to
further examine gender role affects in driving.