TPR-Robina: Toyota’s guide robot

TPR-Robina, Toyota tour guide robot ---

Toyota’s new guide robot, formerly known as ‘DJ Robot’, has officially been named TPR-Robina, according to an August 22 Toyota press release. Photos reveal a slightly more professional look (no more scowling eyes) to go along with the droid’s improved ability to avoid obstacles and operate autonomously, while agile, jointed fingers enable TPR-Robina to grasp writing utensils and sign autographs. Further, in addition to being able to communicate using words and gestures, the 60-kg, 1.2-meter tall robot has an image recognition system that allows it to read visitors’ name tags so that it can tailor its directions accordingly. TPR-Robina will begin working as a receptionist and guide at the Toyota Kaikan Exhibition Hall on August 27.

Source : http://www.pinktentacle.com

Remote Control Hammerhead Shark

Radio Control Hammerhead Shark
If you like having the beach all to yourself, the latest remote control hammerhead shark should help clear a nice area for you. The 24″ water robot, can dive up to 8 feet in water and has a range of approximately 50 feet. The remote control is water resistant and the eyes light up to improve underwater visibility. I want one.
Price: $99


Source : http://www.uberreview.com


Swimming Snake Robot: ACM-R5

Ever scared of snakes around your ankles when you were swimming around in the river? Well, I don’t think you have to worry about that with this robot anytime soon, but Hirose Fukushima Robotics lab has created a creepy but way cool looking robot resembling a snake. “ACM-R5â€? can make it’s way around on the ground and even in water.

Snake Robot via Fukushima Robotics Lab

Snake Joint Diagram via Fukushima Robotics Lab

The joint of ACM-R5 consists of an universal joint and bellows (Fig 4). It was developed on the basis of the previous model HELIX, which was designed for research of spirochete-like helical swimming. An universal joint plays a role of bones, and bellows do a role of an integument. ACM-R5 can form a smooth shape due to this joint structure, and it is important for effective locomotion. To be precise, the universal joint has one passive twist joint at the intersection point of two bending axis to prevent mechanical interference with bellows.

The control system of ACM-R5 is an advanced one. Each joint unit has CPU, battery, motors, so they can operate independently. Through communication lines each unit exchanges signals and automatically recognizes its number from the head, and how many units join the system. Thanks to this system operators can remove, add, and exchange units freely and they can operate ACM-R5 flexibly according to situations.

ACM-R5 is equipped with advanced control system and shows the ability of amphibious snake-like robots to a certain extent. However a large number of problems are remained for realization of practical snake-like robots, both in software and hardware.


Source : http://www.trossenrobotics.com



JHR-Special Issue on "Active Vision of Humanoids"




Following the successful workshop on the Active Vision of Humanoids that
happened in Pittsburgh, PA during the last Conference on Humanoid Robotics
(November 2007)

Practical computer vision-systems are devoted to answering a set of
practical questions, such as is there something moving independently in the
video taken by a moving camera? What is it? Is there a human in the image?
Who is he? On the other hand, humans are involved in an ongoing process of
analyzing images. As Stuart Geman wrote, "real world images have essentially
infinite detail which can be perceived only by a process that is itself
ongoing and essentially infinite. The more you look, the more you see".
Considering a humanoid robot, how should we think about its vision? The way
we think of a practical vision system or the way we think of human vision?

Papers are solicited that keep some focus on the question of the
visual/motor architecture of the humanoid: how should its motion system be
structured? Should it stabilize the images? Segment the scene into surfaces?
Constantly check where it is with regard to its knowledge of the world? How
should it build models of objects? How should it integrate cue information?
How should it reach a decision?
What is its perception of spatial layout? How should it learn, and what
should it learn? Is there software that we have today which can be used to
provide humanoids with a basic visual front-end, and what would this be?
Should we be developing visuo-motor representations?
How could we build them and how could we use them?

Many of the questions raised above are addressed in contemporary computer
vision, but from the perspective of graphics and multimedia, image editing
and image databases. Existing approaches do not apply to the case of a
real-time system moving the way humans do. The peculiarity of humanoid
vision stems from its purpose of supporting the action of an anthropomorphic
body (with hands and legs) as opposed to "just" being pattern recognition
or image understanding.
Thus, in some sense, the humanoid active vision envisioned for this special
issue, constitutes an evolution from the Active Vision of the 90's to the
"Action Vision" of the new millennium. Action Vision considers the motor
system of the humanoid as an integral part of its perceptual machinery.

Papers addressing such topics or others relevant to the design of a
humanoid's vision system, should be submitted before the end of November for
a target publication date of early 2009.

Source : http://publications.csail.mit.edu