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UC San Diego cognitive scientists and engineers are using iRat, a robot rodent, in social neuroscience research that could lead to robots that are better equipped to interact with humans. The researchers, led by cognitive scientist Andrea Chiba, bioengineer Todd Coleman and computer scientist Janet Wiles at the University of Queensland, are studying how their robotic rodent interacts with and triggers responses from rats equipped with state-of-the-art devices that record heart rate, respiration rate and brain activity.
UC San Diego mechanical engineering professor and recent robotics hire James Friend specializes in generating motion. His research teams have built microrobots that allow catheters to navigate through the human body. He has also developed robotic finger joints and a silent, fully articulated neck motor that exceeds human capabilities. At UC San Diego, Friend plans to collaborate across disciplines to create groups of microrobots that work together, similar, for example, to the crawling spiders in the movie “Minority Report.”
Computer science professor Manmohan Chandraker’s research focuses on self-driving cars. Some of the questions he is helping to answer can help robots navigate the real world. Chandraker is a computer vision expert. His work converts 2D images to 3D maps of the world that allow self-driving cars to pinpoint the location of traffic participants such as pedestrians and vehicles. The data are combined with information about the car's surroundings such as lanes, roads and traffic signs. The ultimate goal is scene understanding, especially in crowded environments, that allows the cars to plan their path or predict potential dangers to take evasive action. In addition to cars, the research also could apply to unmanned ground or aerial vehicles.
Context-sensitive robotics systems will come in all shapes and sizes. Picture hundreds of sensor balloons communicating via inexpensive cellphone technology that can be released into a developing hurricane, self-distribute, and track the storm over several days to improve the accuracy of track and intensity forecasts. Mechanical engineer Thomas Bewley and his team are developing this system, which relies on complex controls algorithms. This is just one of many examples of how controls algorithms can be used to open new applications for advanced robotics systems.
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