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Announcing two doctoral student positions in Media Technology at Södertörn University
Human-Robot Interaction in Osaka, Japan
This week several FAL members are attending Human-Robot Interaction 2010 in Osaka. Henriette was co-organizer of the HRI Pioneers Workshop for new researchers in the field, and also presented a poster on attitudes towards robots. Ylva presented a paper in the Collaborations with the Arts Workshop, together with artist Ulla West. Also at this workshop, Lars Erik organized a brainstorm session. Finally, Rob Tieben's video on ActDresses was featured in the video program.
One highlight was the presentations by Japanese companies on the latest robot technology, including Sanrio subsidiary Kokoro, which manufactures many well-known robots, including the Geminoid (together with Osaka University and ATR) and HRP-4c (together with AIST). Can the lifelike Hello Kitty robot be far off? Another highlight was the keynote speech by Kazuhiro Kosuge on the Dance Partner Robot, in which he compared human-robot interaction to a dance with a robot follower reading the human lead. Also, the panel on Social Responsibility in Human-Robot Interaction with Hiroshi Ishiguro, Illah Nourbakhsh, Peter Kahn and Vanessa Evers raised a lot of interesting questions on how robots are presented to the general public and the future we claim to be building as robot researchers.
Below are some pictures of the robots present at the conference reception. The picture above shows the human-robot play we got to see in a traditional Japanese theatre.
Prostate cancer surgeons 'feel' with their eyes; 3-D HD view gives surgeons compensatory illusion of tactile sensation
Portrait Catalog on Video
Push!Music on Video
Watch the video below where Maria Håkansson and Mattias Rost demonstrates Push!Music!
Video of GlowBots
GlowBots are small round robots that displays visually appealing shapes on a color-intense hypnotizing display. Interacting with the robot encourages it to seek out and communicate its shape to other robots. Through their rich interaction a flora of shapes emerges that entices interest and engagement in an open ended fashion for joy and entertainment.
GlowBots are here presented by Mattias Jacobsson.
Video of the week: Context Photography
Here's a description of the concept. Watch the video for a demo of the mobile application!
When taking a picture, would it be possible and interesting to capture something in addition to the visuals of the scenery? We explore if e.g. sound, temperature and pollution could be used as parameters in a digital camera and how these phenomena could be "visualised" or "represented" in a picture. The fundamental idea is to go beyond the traditional parameters (light, speed and focus) used in both analogue and digital cameras, and widen the concept of what a camera can capture. Digital technology opens up for new dimensions that can affect photography! This means that digital cameras no longer have to resemble their analogue counterparts. Unlike the editing of a picture in e.g. Photoshop, we want the (new) parameters to affect the image in real-time.
We have collaborated with a focus group of open-minded and explorative Lomographers, as well as with other dedicated amateur photographers. They were not primarily our end user group, but a source of inspiration (and also participants in design sessions) when designing the camera prototype.
Columbus on Video!
The application is here presented by Mattias Rost.
Meeting with Bestic
Kick-Off workshop of the Playful Experiences project
Playful Experiences is a new project in the Mobile Life Centre. The main purpose of the project is to understand what constitutes enjoyment of using a product; what kinds of experiences the product can elicit, and how to design something that evokes certain kind of experience. The kick-off workshop of the project took place in a beautiful cosy house in Bergianska trädgården, Naturens Hus. Together with 3 researchers from Nokia Research Center in Tampere and a group from the Mobile Life Centre (Ylva, Henriette and Nicolas) discussed and decided what we want to achieve in this project. From the playful experience of flirting to language differences around the word "playfulness", the discussions were intense and promising for the next steps of the projects. You can read more on the project on the Mobile Life website.
SIGGRAPH Asia in Yokohama
I'm back!
Cheers,
Sara Ljungblad
NASA, GM take giant leap in robotic technology
LIREC meeting in London
Walking robot switches gaits autonomously and flexibly
Particle filters
A particle filter is a technique used in computer vision to estimate the state of a system, given noisy data from fallible sensors. The underlying idea is called a hidden markov model, and looks something like this:
The assumption is that any state of the system is dependant on it’s previous state (and thus all previous states) and this state is something we can never know directly, only via observations. There are two very different sources of inaccuracy or noise. One originates in the state change process – as it’s assumed we can never have a complete model of this (a good bet in the case of human actions for example). The other source of noise is in the observation process itself, which comes from the way the sensors work. This is more predictable, and filters of this type are built to allow you to account for this.
Particle filters maintain a multitude of hypotheses of the hidden state of the system at the same time. They attempt to model state changes in some basic way, for instance the velocity of a moving object. They also model the observation process, for example a distance/angle reading of an object in x,y space. Each time a new observation arrives, the system grades each particle’s simulated observation against the incoming one and weights them accordingly.
This is a frame from some particle filter code I’ve written which is tracking an object as described above. The line is pointing to the current estimation which is based on readings from a radar like sensor. I’ve told the system that the heading sensor is less reliable than the distance sensor, and so the particles are spread out in a vague crescent shape accordingly. This shape is called the probability distribution function (or pdf) and it’s a strength of particle systems to model complex pdfs such as this effectively.
