Abstract

As robotic systems are moving from well controlled settings to unstructured environments, they are required to operate in dynamic and cluttered scenes. Finding an object, estimating its pose, and tracking the pose over time in these scenes are challenging problems. Although various approaches have tackled these problems, their scope of objects and robustness of their solutions are still limited. We focus on object perception using visual sensory information, which spans from the monocular camera to the recently appeared RGB-D sensor, and address four important challenges related to the topic of 6-DOF object pose estimation and tracking in unstructured environments.

A large number of 3D object models are widely available in online object model databases, and these object models have significant prior information which includes geometric shapes and photometric appearance. We note that using both geometric and photometric attributes available from the models enables to handle both textured and textureless objects. We present efforts to broaden the spectrum of objects by combining geometric and photometric features.

Another challenge is how to dependably estimate and track the pose of an object in spite of clutter in the background. The difficulties of object perception mainly depend on the degree of clutter. The background clutter is likely to lead to false measurements, and the wrong measurements tend to result in inaccurate pose estimates. We present two multiple pose hypotheses frameworks: a particle filtering framework for tracking and a voting framework for pose estimation.

Speaker Bio

Dr. Henrik I. Christensen is the KUKA Chair of Robotics at the College of Computing Georgia Institute of Technology. He is also the executive director of the Institute for Robotics and Intelligent Machines (IRIM). Dr. Christensen does research on systems integration, human-robot interaction, mapping and robot vision. The research is performed within the Cognitive Robotics Laboratory. He has published more than 300 contributions across AI, robotics and vision. His research has a strong emphasis on “real problems with real solutions”. A problem needs a theoretical model, implementation, evaluation, and translation to the real world. He is actively engaged in the setup and coordination of robotics research in the US (and worldwide). Dr. Christensen received the Engelberger Award 2011, the highest honor awarded by the robotics industry. He was also awarded the “Boeing Supplier of the Year 2011” with 3 other colleagues at Georgia Tech. Dr. Christensen is a fellow of American Association for Advancement of Science. He received an honorary doctorate in engineering from Aalborg University 2014. He collaborates with institutions and industries across three continents.