computer must give all the directions, such as a situation in which a building or similar distraction blocks the trainer’s line of sight.
For the most part, the field trials went smoothly. “Occasionally, we’d forget that the dog didn’t really have a sense that he was carrying one-of-a-kind equipment in a vest on his back,” Britt said. “So, he’d run too close to the side of a building and clip the electronics pack, or he’d slide through a mud puddle and soak the equipment.”
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verall, the project was successful. The computer correctly issued directional commands 99 percent of the time. However, Major’s response to left and right directional commands was only accurate about 80 percent of the time. “You have to understand that dogs see left and right a little differently than we do,” Britt said. “You could give perfect directions, but you didn’t always get the ‘left’ or ‘right’ that you wanted.”
32 Auburn Engineering
Britt used this research project as the topic for his doctoral dissertation. “The most significant thing about this research is that no one has ever autonomously controlled a canine in the manner we demonstrated,” he said. “I guess you could call Major the first autonomous remote-controlled dog.” In August, Britt graduated with a doctorate in computer science and software engineering. His research project will continue under his former team. “We’ve asked for an additional year on the funding from the ONR,” said Bevly. “There won’t be any more funding through that particular program project, but we can tack another year of work onto the resources we already have and then can search for further funding from other sources.” Miller and the undergraduate researchers will take the project to the next level, working towards a better understanding of the directional issues Britt encountered. “Now that we can accurately locate the position and orientation of the canine, the
question becomes what algorithms will be effective in getting the canine where I want it?” Miller said. “Other companies are showing interest in the work now as well, and that gives us the opportunity to expand from our initial goals.” While Britt focused on the use of GPS and machine learning to autonomously control Major, Miller plans to add the use of inertial sensors to the vest and investigate other control strategies. GPS gives position, velocity and course measurements with excellent accuracy, as long as there are enough satellites in view and the location of the satellites is conducive to good estimates.
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owever, GPS measurements are taken at relatively low rates and can be non-existent if the canine moves into areas that have low satellite visibility. So, inertial sensors and magnetometers can be used along with GPS to help out. Low grade inertial sensors, such as gyroscopes and accelerometers, give measurements at high rates and continue to do so even when the canine is indoors and out of