BEGIN:VCALENDAR
VERSION:2.0
PRODID:-//Memento EPFL//
BEGIN:VEVENT
SUMMARY:Computing motions for medical and assistive robots
DTSTART:20141013T140000
DTSTAMP:20260929T060953Z
UID:3d45de795e9cb7fdbf5c00ebf79ca4b451c079d85eda9646884574f3
CATEGORIES:Conferences - Seminars
DESCRIPTION:Dr. Ron Alterovitz\, University of North Carolina\nEmerging ro
 bots have the potential to improve healthcare delivery\, from enabling sur
 gical procedures that are beyond current clinical capabilities to autonomo
 usly assisting people with daily tasks in their homes. In this talk\, we w
 ill discuss new algorithms to enable medical and assistive robots to safel
 y and semi-autonomously operate inside people's bodies or homes. These alg
 orithms must compensate for uncertainty due to variability in humans and t
 he environment\, consider deformations of soft tissues\, guarantee safety\
 , and integrate human expertise into the motion planning process.\nFirst\,
  we will discuss how our new algorithms apply to two recently created medi
 cal devices\, steerable needles and tentacle-like robots\, designed for in
 terventional radiology and neurosurgery procedures. These new devices can 
 maneuver around anatomical obstacles to perform procedures at clinical sit
 es inaccessible to traditional straight instruments. To ensure patient saf
 ety\, our algorithms explicitly consider uncertainty in motion and sensing
  to maximize the probability of avoiding obstacles and successfully accomp
 lishing the task. We compute motion policies by integrating physics-based 
 biomechanical simulations\, optimal control\, parallel computation\, and s
 ampling-based motion planners.\nSecondly\, we will discuss how our new alg
 orithms apply to autonomous robotic assistance for tasks of daily living i
 n the home. We will present demonstration-guided motion planning\, an appr
 oach in which the robot first learns time-dependent features of an assisti
 ve task from human-conducted demonstrations and then autonomously plans mo
 tions to accomplish the learned task in new environments with never-before
 -seen obstacles.\nBio: Dr. Ron Alterovitz is an Assistant Professor in Com
 puter Science at the University of North Carolina at Chapel Hill. He leads
  the Computational Robotics Research Group which investigates new algorith
 ms to enable robots to safely and autonomously complete novel tasks in cli
 nical and home environments. Prior to joining UNC-Chapel Hill in 2009\, Dr
 . Alterovitz earned his B.S. with Honors from Caltech\, completed his Ph.D
 . at the University of California\, Berkeley\, and conducted postdoctoral 
 research at the UCSF Comprehensive Cancer Center and the Robotics and AI g
 roup at LAAS-CNRS (National Center for Scientific Research) in Toulouse\, 
 France. Dr. Alterovitz has co-authored a book on Motion Planning in Medici
 ne\, was co-awarded a patent for a medical device\, and has received multi
 ple best paper finalist awards at IEEE robotics conferences. He is the rec
 ipient of an NIH Ruth L. Kirschstein National Research Service Award\, the
  UNC Computer Science Department's Excellence in Teaching Award\, and an N
 SF CAREER award.
LOCATION:MEB110 http://plan.epfl.ch/?lang=fr&room=MEB110
STATUS:CONFIRMED
END:VEVENT
END:VCALENDAR