{"id":28318,"date":"2019-04-17T21:19:29","date_gmt":"2019-04-18T01:19:29","guid":{"rendered":"https:\/\/www.bu.edu\/cise\/?p=28318"},"modified":"2021-09-21T19:57:24","modified_gmt":"2021-09-21T23:57:24","slug":"how-to-make-self-driving-vehicles-smarter-bolder-2","status":"publish","type":"post","link":"https:\/\/www.bu.edu\/cise\/how-to-make-self-driving-vehicles-smarter-bolder-2\/","title":{"rendered":"How to Make Self-Driving Vehicles Smarter, Bolder"},"content":{"rendered":"

\"\"<\/em>With $7.5M DOD grant, BU researchers head international team developing bioinspired control systems for self-navigated vehicles<\/h2>\n

Autonomous vehicles that can maneuver themselves around any city are already out on our public roads, says Yannis Paschalidis, but operating off-road remains a challenge.<\/p>\n

\u201cThese vehicles are designed for very structured environments, within roads and lanes,\u201d says\u00a0<\/span>Paschalidis<\/a>, a College of Engineering professor of biomedical, systems, and electrical and computer engineering, who uses data science and machine learning to develop new software algorithms and control systems. \u201cThey are only programmed to recognize a small number of different types of objects.\u201d<\/p>\n

Paschalidis has a vision for self-driving vehicles that would launch them from the mundane world of suburban commuting to the most dynamic (and sometimes harsh) places around the globe. \u201cWe are interested in developing fundamental principles that can be applied to autonomous vehicles capable of navigating themselves on the ground, underwater, and in the air,\u201d he says.<\/p>\n

To make that possible, the Department of Defense has awarded $7.5 million in Multidisciplinary University Research Initiative (MURI) funding for Paschalidis to team up with other scientists from Boston University, Massachusetts Institute of Technology, and Australian research universities.<\/p>\n

\u201cOur team spans two continents and brings together some of the preeminent experts in neuroscience\u2014with emphasis on localization, mapping, and navigation functions\u2014with experts in robotics, computer vision, control systems, and algorithms,\u201d says Paschalidis, the team\u2019s principal investigator. \u201cWe\u2019re essentially going to use insights from neuroscience to better organize and control engineered systems.\u201d<\/p>\n

Their goal? To investigate how the brains of living organisms\u2014namely ants, animals, and humans\u2014process their spatial environments to derive meaningful navigation information. The international research team calls their efforts Project NeuroAutonomy.<\/p>\n

\u201cThe research that we\u2019ll be doing under this MURI is focused on the most interesting control system out there\u2014the brain and its coordination of the neurosensory and neuromuscular systems in the body,\u201d says co\u2013principal investigator\u00a0<\/span>John Baillieul<\/a>, an ENG Distinguished Professor of mechanical, systems, and electrical and computer engineering.<\/p>\n

The Australian collaborators, particularly insect navigation expert Ken Cheng of Macquarie University, will draw insight from the way that ants use visual cues to move around. In the United States, BU collaborators will lead teams that examine animal and human spatial navigation.<\/p>\n

\u201cThis project offers the potential for some major theoretical breakthroughs for understanding cognition,\u201d says co\u2013principal investigator\u00a0<\/span>Michael Hasselmo<\/a>, director of BU\u2019s Center for Systems Neuroscience and a College of Arts & Sciences professor of psychological and brain sciences.<\/p>\n

Hasselmo will lead the team\u2019s investigation of how rodents navigate their environment. He says that although this project is focusing on navigation, elements of the algorithm the team plans to develop could eventually be applied \u201cto a broad range of different types of intelligent behavior.\u201d<\/p>\n

To develop the algorithm, the team will zero in on three big gaps between the navigation prowess of current autonomous vehicle technology and biological organisms, says co\u2013principal investigator\u00a0<\/span>Chantal Stern<\/a>, director of BU\u2019s Cognitive Neuroimaging Center. Stern will lead team members in using functional MRI to investigate how humans develop a map of their environment and detect changing elements of their surroundings.<\/p>\n

\u201cAn example that comes directly from robotics is known as the loop closure problem,\u201d Stern says. \u201cWhen you wander around in a circle through your house and come back to the kitchen, you know you are back in the kitchen; you have mapped your environment and recognize that you have returned to a location you were in before. In robotics, that\u2019s a difficult problem for an autonomous system. An autonomous system will keep mapping a location it returns to, in the same way a Roomba vacuum keeps cleaning the same spot when it comes back around to the same location.\u201d<\/p>\n

Having a fully autonomous vehicle accurately map an area of land or water could be a useful application for military operations, allowing foreign landscapes to be charted without human assistance or putting any lives at risk.<\/p>\n

\u201cIf you want to [use autonomous vehicles to] develop an accurate map of an area, then you don\u2019t want [the vehicle] to overwrite the map every time [it returns] to the same place,\u201d says Stern, a CAS professor of psychological and brain sciences.<\/p>\n

Her team will also investigate how humans decide what\u2019s valuable information and what\u2019s visual clutter as they navigate their environment.<\/p>\n

\u201cHow do you determine what is a landmark? For example, we can use the Citgo sign as a landmark, but we don\u2019t tell people to turn right at the UPS truck,\u201d Stern says. \u201cThe UPS truck is not a useful navigational landmark.\u201d In other words, because it\u2019s not a stable part of the environment, the UPS truck is just visual clutter.<\/p>\n

The last problem the team will investigate is how we predict the changing dynamics of an environment.<\/p>\n

\u201cWhen you are driving down the street and see a child or a dog or bicyclist on the side of the road, you are already thinking that they might cross the street and you\u2019ll be prepared for [them] to move,\u201d Stern says. \u201cBut you know the mailbox isn\u2019t going to move. How does the brain do that? How do you understand that prediction?\u201d<\/p>\n

John Leonard, a co\u2013principal investigator and the head of MIT\u2019s Marine Robotics group, says he\u2019s looking forward to making use of recent advances in deep learning and object detection.<\/p>\n

\u201cTaking the best from biologically inspired models and biologically derived models and combining those with real robot experiments is very exciting,\u201d Leonard says. \u201cThe potential impact of the research is awe-inspiring. The fact that memory formation is coupled to how an animal or human knows their position\u2026perhaps could one day lead to better insights that ultimately might lead to better therapies for memory.\u201d<\/p>\n

Paschalidis, Project NeuroAutonomy\u2019s team leader, predicts the biggest challenge for the team is that it will be impossible to read the \u201ccode\u201d that animals and humans use to navigate.<\/p>\n

\u201cWe have to infer that code from observations that we make,\u201d he says. \u201cThe second challenge will be to translate those observations into specific, detailed control policies [for autonomous vehicles].\u201d<\/p>\n

The US-based team also includes\u00a0<\/span>Margrit Betke<\/a>, a CAS professor of computer science,\u00a0<\/span>Roberto Tron<\/a>, an ENG assistant professor of mechanical engineering, and from MIT, Nicholas Roy, a professor of aeronautics and astronautics.<\/p>\n

By Kat J. McAlpine (originally published on BU Today, April 17, 2019)<\/h3>\n

Kat J. McAlpine can be reached at katjmcal@bu.edu.<\/em><\/p>\n","protected":false},"excerpt":{"rendered":"

With $7.5M DOD grant, BU researchers head international team developing bioinspired control systems for self-navigated vehicles Autonomous vehicles that can maneuver themselves around any city are already out on our public roads, says Yannis Paschalidis, but operating off-road remains a challenge. \u201cThese vehicles are designed for very structured environments, within roads and lanes,\u201d says\u00a0Paschalidis, a […]<\/p>\n","protected":false},"author":18553,"featured_media":28321,"comment_status":"closed","ping_status":"open","sticky":false,"template":"","format":"standard","meta":[],"categories":[201],"tags":[],"_links":{"self":[{"href":"https:\/\/www.bu.edu\/cise\/wp-json\/wp\/v2\/posts\/28318"}],"collection":[{"href":"https:\/\/www.bu.edu\/cise\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.bu.edu\/cise\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.bu.edu\/cise\/wp-json\/wp\/v2\/users\/18553"}],"replies":[{"embeddable":true,"href":"https:\/\/www.bu.edu\/cise\/wp-json\/wp\/v2\/comments?post=28318"}],"version-history":[{"count":1,"href":"https:\/\/www.bu.edu\/cise\/wp-json\/wp\/v2\/posts\/28318\/revisions"}],"predecessor-version":[{"id":28322,"href":"https:\/\/www.bu.edu\/cise\/wp-json\/wp\/v2\/posts\/28318\/revisions\/28322"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.bu.edu\/cise\/wp-json\/wp\/v2\/media\/28321"}],"wp:attachment":[{"href":"https:\/\/www.bu.edu\/cise\/wp-json\/wp\/v2\/media?parent=28318"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.bu.edu\/cise\/wp-json\/wp\/v2\/categories?post=28318"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.bu.edu\/cise\/wp-json\/wp\/v2\/tags?post=28318"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}