Computer Vision,
Dr Grzegorz Cielniak,
Dr Nicola Bellotto,
Dr Oscar Martinez Mozos,
Google,
Google Faculty Research Award,
Lincoln Centre for Autonomous Systems,
quality of life technologies,
Research,
robots,
School news
Computer scientists are developing new adaptive mobile technology which could enable blind and visually-impaired people to ‘see’ through their smartphone or tablet. Funded by a Google Faculty Research Award, specialists in computer vision and machine learning based at the University of Lincoln, UK, are aiming to embed a smart vision system in mobile devices to […]
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A project involving 3D camera technology currently being developed at the University of Lincoln, UK, could result in a fully automatic robotic harvesting system for broccoli. The University of Lincoln was one of more than 70 UK businesses and universities to share funding through the £70 million Agri-Tech Catalyst, which aims to improve the development […]
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On Wednesday 3rd June 2015, Dr Massimiliano Di Luca from the School of Psychology, University of Birmingham, will give a research seminar in the School of Computer Science. Everyone is welcome! When: Wednesday 3rd June 2015 @ 4:00pm Where: MC0024, MHT Building Title: Multisensory Perception of Soft Objects Abstract Softness is the subjective impression of the physical deformability […]
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‘We are pleased to inform you that your article “A Computational Modelof Human-Robot Spatial Interactions Based on a Qualitative TrajectoryCalculus” has been published in Robotics and is available online’That’s some great news on a Monday morning. So, …
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Everybody in Lincoln is invited to learn about some exciting research in robotics done by my friend and former colleague Sebastian:
Time/Date: 4pm, Tuesday, 1 Oct 2013
Venue: MB1015, Main Admin Building
Speaker: Dr. Sebastian Wrede, Cognitive Systems Engineering, CoR-Lab, Bielefeld University
Title: Kinesthetic Teaching of Redundant Robots in Task and Configuration Space
Abstract: The recent advent of compliant and kinematically redundant robots poses new research challenges for human-robot interaction. While these robots provide high flexibility for the realization of complex applications, the gained flexibility generates the need for additional modeling steps and the definition of criteria for redundancy resolution constraining the robot’s movement generation. The explicit modeling of such criteria usually require experts to adapt the robot’s movement generation subsystem. A typical way of dealing with this configuration challenge is to utilize kinesthetic teaching and guide the robot to implicitly model the specific constraints in task and configuration space. However, in this presentation we report on experiments showing that current programming-by-demonstration approaches are not efficient for kinesthetic teaching of redundant robots and typical teach-in procedures are too complex for novice users. In order to enable non-experts to master the configuration and programming of a redundant robot in the presence of non-trivial constraints such as confined spaces, the talk presents a new interaction scheme combining kinesthetic teaching and learning within an integrated system architecture. The approach was evaluated in a user study with 49 industrial workers in a medium-sized manufacturing company. Results show that the interaction concepts implemented on a KUKA Lightweight Robot IV are easy to handle for novice users, demonstrate the feasibility of kinesthetic teaching for implicit constraint modeling in configuration space and yield significantly improved performance for the teach-in of trajectories in task space.
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