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Welcome to the July 2010 Issue of the Electronix Express Newsletter
STORIES
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Drug addiction is a complex process that involves numerous biological and environmental factors, but a central element is how the drugs affect the activity of dopamine, the chemical that regulates pleasure and reward in the brain. To get a real-time sense of dopamine activity, Joanna Fowler and her colleague Gene-Jack Wang at Brookhaven, along with Nora Volkow, Director of the National Institute on Drug Abuse, combined positron emission tomography (PET), a medical imaging technology useful for identifying brain diseases, with special radioactive tracers that bind to dopamine receptors. The PET scan highlights the movement of the tracers in the brain, and can be used to reconstruct real-time 3D images of the dopamine system in action.
The scientists tested this procedure on several drug-addicted volunteers as well as healthy control subjects of the same age. Their findings indicate that people with addictions in general have 15-20 percent fewer dopamine receptors than normal and thus cannot bind to a lot of the dopamine released in response to the drugs or natural reinforcers like food. According to the study, the addicted individuals all had a blunted dopamine response. As noted by Fowler, "this reinforces the idea that drug addicts experience diminished feelings of pleasure, which drives their continual drug use." The highlights of this study were recently presented in Fowler's talk, "Imaging Brain Chemistry in Diseases of Addiction," at the American Society for Biochemistry and Molecular Biology's annual meeting, which took place April 26 in Anaheim, CA
TACO (Threedimensional Adaptive Camera with Object detection and foveation) is a European Commission co-financed small or medium-scale focused research project under the 7th Framework Program. The project started in February and the duration is defined for 30 months. TACO employs 3D foveation to significantly improve on current 3D sensor systems. Foveation enables the TACO systems to acquire 3D images with coarse level of details. This allows for fast object detection techniques to select areas of interest in the coarse 3D image and then concentrate image acquisition of regions or details of interest. In short, the robot will become able to focus on the most relevant object and scan and monitor it closely and detailed, similar to the human eye.
The TACO sensor will enable significantly better, faster and cheaper 3D sensing compared to current laser scanners. TACO's consortium is composed of four research institutes, two industrial companies and one university, which are all seated in Europe (Austria, UK, Germany and Norway). The expertises of the consortium members are widespread and range from the development of the required hardware and software components to the provision of the test environment to the experience of international project coordination.
Mirko Kovac is a young robotics engineer who has already made leaps forward in the field with his grasshopper-inspired jumping robot. He and his collaborators have created an innovative perching mechanism where the robot flies head first into the object, a tree for example -- without being destroyed -- and attaches to almost any type of surface using sharp prongs. It then detaches on command. The goal is to create robots that can travel in swarms over rough terrain to come to the aide of catastrophe victims. "We are not blindly imitating nature, but using the same principles to possibly improve on it," explains Kovac, who recently finished his doctoral studies as EPFL. "Simple behavioral laws such as jumping, flying and perching lead to complex control over movement without the need for high computational power."
This new form of Artificial Intelligence (AI) takes its inspiration from the insect world, but is more as an abstract reflection on their instincts and design principles than merely imitating their morphology. This simplicity allows for greater mobility since the robots are not bogged down with heavy batteries. Kovac imagines swarms of his robots equipped with different sensors and small cameras that could be deployed over devastated areas to transmit essential information back to rescue command centers. "I am fascinated by the creative process, and how it is possible to use the sophistication found in nature to create something completely new," remarks Kovac. The perching mechanism can be easily adapted to other robots. His previous robot, a quarter-gram jumping robot that can achieve heights of up to four and a half feet, could now be fitted with the new perching mechanism as well as wings, thus creating a hybrid creature that gets around much like a flying grasshopper.
Much like a human child, the robot learns from experience how to respond to emotions displayed by people around it. If someone shows fear or cries out in pain, the robot may learn to change its behavior to appear less threatening, backing away if necessary. If someone cries out in happiness, it may even detect the difference, and be able to one day fine tune its responses to individuals. Robots that can adapt to people's behaviors are needed if machines are to play a part in society, such as helping the sick, the elderly, people with autism or house-bound people, working as domestic helpers, or just for entertainment. The main idea is by being more in tune with human emotions, the robots should be more readily accepted by the people they may one day serve.
The three-year, Sixth Framework Program project involves six countries and 25 specialists who are building demonstration robots as proof of concept. The work is still well shy of an I Robot scenario with emotionally complex machines taking matters into their own hands, but the empathy empowering software being developed by Feelix Growing is a big step forward for robotics.
Dr. Manoonpong, computational neuroscientist at the University of Goettingen in Goettingen, Germany is one of the creators of the Runbot. The Runbot uses sensors and an infrared eye to detect a slope on its path and adjust on the spot! The robot's ability to switch quickly from one gait to another is due to the organization of the movement control. On the more basic levels, movement is based on reflexes driven by sensors. Control circuits ensure that the joints are not overstretched or that the next step is started as soon as the foot touches the ground. It's created with the same critical joints as a human. "It has two hip joints, two knee joints, here ... and it has a foot contact sensor for each leg." Dr. Mannonpong said. Just like in people, sensors make sure the joints are not over-stretched and that the next step is initiated as soon as the foot touches the ground. This technology may someday be used to help humans.
Speed walking robots started out slowly, at 0.7 leg lengths per second. Now, the Runbot can speed walk at 3.5 leg lengths per second. Runbot holds the world record in speed walking for dynamic machines. Just like a human, it leans forward slightly and uses shorter steps. It can learn this behavior after only a few trial runs. Compared to its size, that's almost as fast as a speed walking Olympian. Proving robots are moving us fast towards the future.
The robot's hardware was developed by FerRobotics, PROFACTOR's partner of many years. An intelligent 3D object recognition system creates a model of the real situation of the workpieces, which is then transmitted to a touch panel. The robot processes this information, proposing virtual gripping points on the panel. Should these points not be optimal in the operator's view, he can intervene in the process by simply marking new gripping points on the display. The system learns the new gripping points, storing in a database this knowledge along with the corresponding workpieces. The stored knowledge is subsequently retrieved to solve similar problems during later process execution. The system thus co-learns in operation and is successively capable of solving tasks independently, in this way achieving a greater degree of autonomy.
This co-learning process technology is referred to as augmented reality and is becoming increasingly important in robotics. With augmented reality technology, computer-generated virtual objects are superimposed visually on real objects, enabling appropriate responses to situations in real working environments. "For instance, a virtual image of repair procedures could be displayed on data glasses worn by a maintenance technician at work," Pichler noted. Thus reality is supplemented by an additional level, which is the reason this technology is often referred to as augmented reality.
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