To accelerate the field, research in a number of key areas needs to be undertaken. It ranges from fundamental long‐term research to practical ready‐to‐deploy developments, as enumerated in that order below:
Visual object recognition: Our robots today are not very aware of their surroundings, as we do not have general‐purpose vision algorithms that can recognize particular objects never seen before as an instance of a known class. (a two‐year‐old child can instantly recognize most chairs as chairs even if they haven’t seen one that looks exactly the same before.)
Manipulation: Our robots today are not very dexterous as we have hardly had any multifingered hands to work with. When mobile robot platforms started becoming available to researchers in the 80’s and 90’s the field of intelligent robot navigation exploded. We need to develop widely deployable robot hands so that hundreds of researchers can experiment with manipulation.
New sensors: Some sensors that robots need have been made incredibly inexpensive by other market pulls, e.g., digital cameras continue to have their price driven down by the cell phone market. But dense touch sensors, 3‐d range sensors, and exotic rf and capacitance sensors are still very hard to come by. Direct investment in new sensor modalities for robots will lead to new algorithms that can exploit them and make robots more aware of their surroundings, and hence able to act more intelligently.
Materials science: Materials science is producing radically new materials with sometimes hard‐to‐believe properties. At the moment, robotics sits on the sidelines and uses these new materials as they might be applicable. A focused program on materials science and robotics would couple researchers in the two fields together to ensure that new materials that specifically benefit robotics are investigated and invented.
Distributed and networked robots: Technology allows us to decompose tasks in ways that humans are incapable. New architectures for robotic components that can self‐assemble, whether physically or virtually, will enable new approaches to many application areas. Awareness of people: most future applications of robots will require that they work in close proximity to humans (unlike today’s manufacturing robots that are so dangerous that people must be kept away). To do so safely, we need both perceptual awareness of people, and actuators and robots that are intrinsically safe for humans to physically contact.
Social interaction: if ordinary people are to work with robots they must be able to interact with them in cognitively easy ways. Our robots can make this possible if they both pick up on social cues from humans (who naturally give such cues to robots, to the surprise of many engineers) and give social signals about their own intentions that a person can easily interpret.
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