Dear Colleagues,
We are pleased to announce that the Robotics 2021 Travel Award and the
Robotics 2022 Travel Award have officially merged since most of the
conferences related to the robotics field will be held in 2022.
Additionally, at this particular moment of the COVID-19 pandemic,
participants of virtual conferences are also welcome to apply for the
award. Given all the above, applications are still open, and the new
submission deadline is 30 June 2022.
The applications will be assessed by an evaluation committee consisting
of senior scholars from the Robotics Editorial Board.
This prize provides financial support for the winners to attend an
international conference (physical or virtual) in the fields related to
robotic systems, to be held in 2021 and 2022, where they will deliver a
presentation, present a poster, or both.
Candidate Requirements:
– Ph.D. graduate or Ph.D. student (proof required);
– Plans to attend an international conference (physical or virtual) in
2021 and 2022 (oral presentation or poster).
Required Application Documents:
– Information about the conference that the applicant is planning to
attend and the abstract that will be submitted;
– Curriculum vitae and list of publications;
– Justification letter describing the focus of the research (max. 800
words);
– Letter of recommendation from at least one supervisor.
The winners (two awardees) will each be awarded CHF 800 and a certificate.
Please apply by clicking the link
(https://www.mdpi.com/journal/robotics/awards/1057) before 30 June 2022.
Prizes will be awarded at the end of July 2022 and announced on the
Robotics website.
Kind regards,
Charlene Dong
Managing Editor
Robotics Editorial Office
Robotics, Volume 10, Issue 3 (September 2021) - 26 articles
https://www.mdpi.com/2218-6581/10/3
Table of Contents
*Cover Story*
Article: The Wearable Robotic Forearm: Design and Predictive Control of
a Collaborative Supernumerary Robot
Vighnesh Vatsal and Guy Hoffman
Robotics 2021, 10(3), 91; doi:10.3390/robotics10030091
*General*
Review: Socially Assistive Robots Helping Older Adults through the
Pandemic and Life after COVID-19
Cristina Getson and Goldie Nejat
Robotics 2021, 10(3), 106; doi:10.3390/robotics10030106
Article: Effects of Temperature and Mounting Configuration on the
Dynamic Parameters Identification of Industrial Robots
Andrea Raviola, Roberto Guida, Andrea De Martin, Stefano Pastorelli,
Stefano Mauro and Massimo Sorli
Robotics 2021, 10(3), 83; doi:10.3390/robotics10030083
Article: The WL_PCR: A Planning for Ground-to-Pole Transition of
Wheeled-Legged Pole-Climbing Robots
Yankai Wang, Qiaoling Du, Tianhe Zhang and Chengze Xue
Robotics 2021, 10(3), 96; doi:10.3390/robotics10030096
Article: Kinematic Synthesis and Analysis of the RoboMech Class Parallel
Manipulator with Two Grippers
Zhumadil Baigunchekov, Med Amine Laribi, Azamat Mustafa and Abzal Kassinov
Robotics 2021, 10(3), 99; doi:10.3390/robotics10030099
*Agricultural and Field Robotics*
Article: A Case Study on Improving the Software Dependability of a ROS
Path Planner for Steep Slope Vineyards
Luís Carlos Santos, André Santos, Filipe Neves Santos and António Valente
Robotics 2021, 10(3), 103; doi:10.3390/robotics10030103
*Industrial Robots & Automation*
Article: Robot-Assisted Glovebox Teleoperation for Nuclear Industry
Ozan Tokatli, Pragna Das, Radhika Nath, Luigi Pangione, Alessandro
Altobelli, Guy Burroughes, Emil T. Jonasson, Matthew F. Turner and
Robert Skilton
Robotics 2021, 10(3), 85; doi:10.3390/robotics10030085
*Medical Robotics and Service Robotics*
Article: Multidirectional Overground Robotic Training Leads to
Improvements in Balance in Older Adults
Lara A. Thompson, Mehdi Badache, Joao Augusto Renno Brusamolin, Marzieh
Savadkoohi, Jelani Guise, Gabriel Velluto de Paiva, Pius Suh, Pablo
Sanchez Guerrero and Devdas Shetty
Robotics 2021, 10(3), 101; doi:10.3390/robotics10030101
*Intelligent Robots and Mechatronics*
Review: Reinforcement Learning for Pick and Place Operations in
Robotics: A Survey
Andrew Lobbezoo, Yanjun Qian and Hyock-Ju Kwon
Robotics 2021, 10(3), 105; doi:10.3390/robotics10030105
*Sensors and Control in Robotics*
Review: Trends in the Control of Hexapod Robots: A Survey
Joana Coelho, Fernando Ribeiro, Bruno Dias, Gil Lopes and Paulo Flores
Robotics 2021, 10(3), 100; doi:10.3390/robotics10030100
...
*Special Issues Open for Submissions*
Resilient Robotic Systems
(Deadline: 15 October 2021)
Kinematics and Robot Design IV, KaRD2021
(Deadline: 15 October 2021)
Industrial Robotics in Industry 4.0
(Deadline: 31 October 2021)
Robots for Health and Elderly Care
(Deadline: 31 October 2021)
Robotics and AI
(Deadline: 15 November 2021)
To access the full list of *Special Issues*, please click here
https://www.mdpi.com/journal/robotics/special_issues
*Upcoming Partner Conferences*
2nd International Conference on Robotics, Intelligent Automation and
Control Technologies (RIACT 2021) (virtual conference, 23–25 September 2021)
The 2021 IEEE/RSJ International Conference on Intelligent Robots and
Systems (IROS 2021) (Online, 27 September 2021)
19th International Conference on Practical Applications of Agents
and Multi-Agent Systems (PAAMS 21) (Salamanca, Spain, 6–8 October 2021)
The 4th International Conference on Intelligent Technologies and
Applications (INTAP 2021) (Grimstad, Norway, 11–13 October 2021)
The 6th International Conference on Data Processing and Robotics
(ICDPR 2022) (Sapporo, Japan, 6–8 January 2022)
To access all conferences, please click here
https://www.mdpi.com/journal/robotics/events#panel-partner-conferences
MDPI
Postfach, CH-4020 Basel, Switzerland
Office: St. Alban-Anlage 66, CH-4052 Basel, Switzerland
Tel. +41 61 683 77 34
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www.mdpi.com
LinkedIn
https://www.linkedin.com/in/robotics-mdpi-319297154/detail/recent-activity/
Twitter @RoboticsMDPI
We’re looking for a scientific software developer with Machine Learning (ML) expertise (MSc or PhD in ML).
Together with our current mathematics and Machine Learning developers, you will work on developing new functionality where state-of-the-art ML techniques are applied to problems in computational chemistry.
https://www.scm.com/news/job-opening-software-developer-machine-learning-in…
Dr. S.J.A. van Gisbergen
Directeur
Software for Chemistry & Materials B.V.
De Boelelaan 1083
1081 HV Amsterdam, The Netherlands
E-mail: vangisbergen(a)scm.com
http://www.scm.com
NEUROMORPHIC COMPUTING NETHERLANDS (NCN2021)
https://www.cwi.nl/research/groups/machine-learning/events/workshop-on-neur…
We kindly invite you to the Neuromorphic Computing Netherlands (NCN2021) Workshop (hybrid). Neuromorphic Computing is rapidly emerging as the principle paradigm for EdgeAI. In this workshop, we aim to bring together researchers and practitioners from algorithmic, architectural and application domains in the Netherlands.
When: 24-09-2021 from 12:50 to 17:00 (Europe/Amsterdam / UTC200)
Where: CWI Amsterdam and online (hybrid)
Contact: Sander.Bohte(a)cwi.nl<mailto:Sander.Bohte@cwi.nl> (Please send an email with your name and affiliation if you would like to attend virtually so we can track the participants)
Zoom link:
https://cwi-nl.zoom.us/j/86293297870?pwd=aWR0alphM1A0MHFXNWUySFRVanI4QT09
Program:
12:50h Opening
13:00h Keynote by Elisabetta Chicca (RUG)
13:50h break
14:00h Federico Corradi (IMEC). Spike-based neuromorphic computing for the edge
14:25h Jesse Hagenaars (TUD). Self-supervised learning of event-based optical flow with spiking neural networks
14:50h Mahyar Shahsavari (RU). A Reconfigurable Neuromorphic Design and the SPIKERFERENCE Project
15:15h posters / break
16:00h Bojian Yin (CWI). Efficient and Effective Spiking Recurrent Neural Networks
16:25h Thomas Tiotto (RUG)
16:50h drinks
Organizers:
Sander Bothe (CWI)
Federico Corradi (IMEC)
Pablo Lanillos (Donders, RU)
This workshop is organized as part of the Efficient Deep Learning NWO-TTW Perspectief programme.
More info: https://www.cwi.nl/research/groups/machine-learning/events/workshop-on-neur…
---
Dr. Pablo Lanillos
www.therobotdecision.com
Tenured assistant professor in Cognitive Artificial Intelligence | AI Robotics Lab
ELLIS Nijmegen Unit
Donders Institute for Brain, Cognition and Behaviour, the Netherlands
p.lanillos @ donders.ru.nl
Dear Robotics Enthusiasts,
are you looking for a postdoc opportunity where you can combine quadrupedal locomotion, articulated soft robots, machine learning, control theory, and many other things?
Then check out this position that Cosimo Della Santina and myself (Jens Kober) have opened at TU Delft - Mechanical Engineering (Cognitive Robotics department), as part of the EU-H2020 project Natural Intelligence (https://www.nih2020.eu/<https://urldefense.proofpoint.com/v2/url?u=https-3A__www.nih2020.eu_&d=DwMF…>).
This is a two year position, salary and benefits are in accordance with the Collective Labour Agreement for Dutch Universities (salary indication: € 3.491 - € 4.402).
You can find more information at the following links
· Call: https://www.academictransfer.com/en/302914/postdoc-efficient-quadrupedal-lo…<https://urldefense.proofpoint.com/v2/url?u=https-3A__www.academictransfer.c…>
· Cosimo's website: https://cosimodellasantina.eu/<https://urldefense.proofpoint.com/v2/url?u=https-3A__cosimodellasantina.eu_…>
· Jens's website: http://www.jenskober.de/<https://urldefense.proofpoint.com/v2/url?u=http-3A__www.jenskober.de_&d=DwM…>
Tackling the challenging goals discussed in the Job Description requires a unique combination of algorithmic/theoretical and experimental skills. Research experience in at least one of the following fields is mandatory: Robot locomotion, Reinforcement learning, Deep Learning, Articulated Soft/Flexible Robots. A basic understanding of the others is greatly appreciated, as well as experience with real robot applications, managing younger researchers, and good programming skills.
Please, do not hesitate to reach out to us in case you have any questions about the position!
If you are interested, please read the application procedure carefully (bottom paragraph in the call).
You can apply online. We will not process applications sent by email and/or post.
----------------
Some quick facts about TU Delft and CoR:
Delft University of Technology (TUD) is the oldest and largest technical university in the Netherlands, with over 23,000 students and 3,300 scientific staff. Its high quality teaching standards and experimental facilities are renowned, placing it among the 6th top universities in Europe and 15th in the world in the Engineering and Technology fields, and 2nd top universities in Europe and 5th in the world in the Mechanical, Aeronautical, and Manufacturing Engineer (QS Ranking 2020). It is a member of the IDEA League, a strategic alliance of five of Europe's leading universities of technology.
TU Delft comprises eight faculties: among these is the 3mE Faculty (Mechanical, Maritime and Materials Engineering), which hosts the Cognitive Robotics (CoR) department. In 2012, TU established the Delft Robotics Institute, in which CoR takes part. The Institute unites all the university's research in the field of robotics, bringing together more than 150 scientific staff from six TU Delft faculties. The aim is to get robots and humans to work together effectively in unstructured environments, and real-world settings. Both the 'hard' robotics disciplines (mechatronics, embedded systems, control and AI) and the 'soft' ones (human-machine interaction, user interaction, architecture, ethics and design) are represented. A part of the Institute is the TU Delft Digital Innovation Hub called RoboValley (https://robovalley.com<https://urldefense.proofpoint.com/v2/url?u=https-3A__robovalley.com_&d=DwMF…>) established to foster collaboration with companies and technology transfer.
Dear all,
This is the zoom link for the CWI Machine Learning Seminar tomorrow
afternoon:
https://cwi-nl.zoom.us/j/83113639352?pwd=U2NtVC9kWmJkY3NOOGdTMUVSVHorUT09
[Meeting ID: 831 1363 9352 Passcode: 551343]
Speaker: Johanna Ziegel (University of Bern)
Title: Valid sequential inference on probability forecast performance
Date: Friday 10 September, 14:00
Location: CWI L016 and on Zoom (link above)
This seminar will be held live at reduced capacity, and will be
live-streamed on zoom for remote attendance.
Please find the abstract below.
Hope to see you then.
Best wishes,
Wouter
Details:
https://portals.project.cwi.nl/ml-reading-group/events/valid-sequential-inf…
============
Valid sequential inference on probability forecast performance
Johanna Ziegel (University of Bern)
Probability forecasts for binary events play a central role in many
applications. Their quality is commonly assessed with proper scoring
rules, which assign forecasts a numerical score such that a correct
forecast achieves a minimal expected score. In this paper, we construct
e-values for testing the statistical significance of score differences
of competing forecasts in sequential settings. E-values have been
proposed as an alternative to p-values for hypothesis testing, and they
can easily be transformed into conservative p-values by taking the
multiplicative inverse. The e-values proposed in this article are valid
in finite samples without any assumptions on the data generating
processes. They also allow optional stopping, so a forecast user may
decide to interrupt evaluation taking into account the available data at
any time and still draw statistically valid inference, which is
generally not true for classical p-value based tests. In a case study on
postprocessing of precipitation forecasts, state-of-the-art forecasts
dominance tests and e-values lead to the same conclusions.
A vacancy for a postdoc is available at our department (Data Analysis and Mathematical Modelling) of Ghent University.
Scientific research is broadly defined and can be about data analysis or mathematical modelling for natural and biological processes applied in one or more research areas at our faculty of bioscience engineering.
One possible topic includes experimental design problems within the field of machine learning (e.g. active learning, optimum designs for neural networks, ...)
There is a 30% teaching duty in Dutch associated to the position.
For more info and the application procedure, click here<https://career012.successfactors.eu/career?company=C0000956575P&career_job_…>
Deadline for application is 24/09
[cid:image001.png@01D75C87.92473700]<https://www.ugent.be/bw>
Prof. dr. Stijn Luca
Assistant professor
T +32 9 264 59 34
Department Data Analysis and Mathematical Modelling
Research Unit BIOSTAT: Biostatistics
www.biostat.ugent.be<http://www.biostat.ugent.be/>
Campus Coupure, Block A 1st floor 110.068, Coupure links 653, B-9000 Ghent, Belgium directions<https://www.google.com/maps/dir/Coupure+Links+653,+9000+Gent/@51.0527795,3.…>
T administration office +32 9 264 59 32
www.ugent.be<https://www.ugent.be/bw/en>
e-maildisclaimer<https://helpdesk.ugent.be/e-maildisclaimer.php>
Dear all,
It is my pleasure to announce the following CWI Machine Learning seminar.
Speaker: Johanna Ziegel (University of Bern)
Title: Valid sequential inference on probability forecast performance
Date: Friday 10 September, 14:00
Location: CWI L016 and on Zoom (link will follow)
This seminar will be held live at reduced capacity, and will be
live-streamed on zoom for remote attendance.
Please find the abstract below.
Hope to see you then.
Best wishes,
Wouter
Details:
https://portals.project.cwi.nl/ml-reading-group/events/valid-sequential-inf…
============
Valid sequential inference on probability forecast performance
Johanna Ziegel (University of Bern)
Probability forecasts for binary events play a central role in many
applications. Their quality is commonly assessed with proper scoring
rules, which assign forecasts a numerical score such that a correct
forecast achieves a minimal expected score. In this paper, we construct
e-values for testing the statistical significance of score differences
of competing forecasts in sequential settings. E-values have been
proposed as an alternative to p-values for hypothesis testing, and they
can easily be transformed into conservative p-values by taking the
multiplicative inverse. The e-values proposed in this article are valid
in finite samples without any assumptions on the data generating
processes. They also allow optional stopping, so a forecast user may
decide to interrupt evaluation taking into account the available data at
any time and still draw statistically valid inference, which is
generally not true for classical p-value based tests. In a case study on
postprocessing of precipitation forecasts, state-of-the-art forecasts
dominance tests and e-values lead to the same conclusions.