[robotics-worldwide] [journals] Deadline extension! -- ROBOTICS AND AUTONOMOUS SYSTEMS SI on Multimodal Sensor-based Robot Control
andrea.cherubini at lirmm.fr
Tue Sep 6 01:08:47 PDT 2016
Due to numerous requests, we have decided to extend the submission deadline for our RAS SI on Multimodal Sensor-based Robot Control, to OCTOBER 30th, 2016.
Following the success of our "Workshop on multimodal control for HRI" at IROS15 (which will also take place at IROS16):
It is our pleasure to announce the following call for papers:
ROBOTICS AND AUTONOMOUS SYSTEMS
Special Issue on multimodal sensor-based robot control for interaction, soft manipulation and whole body control
Recent technological developments on bio-inspired sensors have made them affordable and lightweight, and therefore eased their use on robots, in particular on anthropomorphic ones (e.g., humanoids and dexterous hands). These sensors include RGB-D cameras, tactile skins, force/moment transducers, and capacitive proximity sensors.
Historically, heterogeneous sensor data was fed to fusion algorithms (e.g., Kalman or Bayesian-based methods) to provide state estimation for modelling the environment. However, since these sensors generally measure different physical phenomena, it is preferable to use them directly in the low-level servo controller rather than to apply multi-sensory fusion, or to design complex state machines. This idea, originally proposed in the hybrid position-force control paradigm, when extended to feedback from multiple sensors, brings new challenges to the controller design; e.g. related to the sensors characteristics (synchronisation, hybrid control, task compatibility, etc.) or to the task representation.
However, this approach represents at best many of our cognitive processes (which directly link perception and action), and is fundamental in many innovative robotic applications, such as human-robot interaction, soft material manipulation, and whole-body control.
Human-robot interaction for collaborative tasks often relies on force/tactile feedback to transmit the user intention to the robot. However, the robot should be capable of recognising the intention even without direct contact between the two. A possible solution comes from visual data, which should then be combined with haptics to obtain the best result.
The automatic manipulation of soft materials (e.g., in the food industry) represents a second important case study. The natural evolution of recent works on vision-based servoing of soft objects, is the integration of haptics and force feedback.
Whole-body control is a third field of research that would greatly profit from the discussed methods. In fact, multiple tasks (manipulation, self collision avoidance, etc.) can be simultaneously realised by exploiting the diverse sensing capabilities of the robot body, which are often bio-inspired.
This special issue aims at consolidating some recent developments in the area of multimodal servo-control, based on a variety of feedback signals, including vision (2D and 3D), touch (haptics), position, force, proximity (from capacitive measurements) etc.
Topics of interest
• hands-on applications where multimodal control is necessary,
• whole-body control with heterogeneous sensors,
• bio-inspired approaches to multimodal control,
• theoretical foundations of multimodal control (e.g., task frame approaches or constraint-based task specification),
• new trends in sensor-based control, based on perspective integration with other modalities (e.g: visual deformation servoing, tactile/haptic servoing, proximity servoing).
Submission deadline: October 30, 2016
Final decision notification: April 30, 2017
Andrea Cherubini, LIRMM University of Montpellier, France
Youcef Mezouar, Institut Pascal, Sigma Clermont
David Navarro-Alarcon, The Chinese University of Hong Kong
Juan Antonio Corrales-Ramon, Institut Pascal, Sigma Clermont
The submission website is located at:
To ensure that all manuscripts are correctly identified for inclusion into the special issue, it is important that authors select “VSI:Multimodal robot control” when they reach the “Article Type Name” step in the submission process.
Associate Professor - MCF
Responsable Master Robotique
LIRMM / Université de Montpellier
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