Lead AI & Robotic of BMW, director of RoboTac Lab, Radboud University, Nijmegen, the Netherlands
Deep Cross-Modal Learning for Object Grasp and Manipulation in Robotics.
For robots to execute tasks in unstructured environments, visuo-tactile plays a key role. The vision-based technologies have become essential for an effective analysis of the scene, path planning, and observing the behavior of humans in the robot workspace. However, vision alone is often not enough to achieve sufficient perception capabilities of robotic systems in unstructured environments, due to variable light conditions, occlusions in cluttered scenes, and a requirement for contact information between robot and environment. Tactile perception is of fundamental importance for robots that physically interact with the external environment. Wisely leveraging tactile information provides robots with enhanced perceptive capabilities. For these reasons, interactive tactile perception is becoming important research directions to support visual perception. Even though tactile and visual perception has gained a great deal of interest, the field of active visuo-tactile interactive perception and cross-modal learning have not been profusely explored in robotics. A robotic system with active visuo-tactile perception and cross-modal learning capability can leverage a priori knowledge acquired with one modality and efficiently use it with other at execution time. In this talk, I will present our recent developed full-fledged active visuo-tactile perception and deep-cross modal learning framework for the robotics systems to efficiently localize cluttered objects in an unknow workspace and to recognize objects, previously inspected with one modality like vision, via tactile modality.
Invité par Daniel Shulz
Short Bio of Mohsen Kaboli
Dr. Mohsen Kaboli is an assistant professor and lead for Robotics, AI, and Tactile Intelligence at BMW Group, Germany and Donders Institute for Brain and Cognition, Radboud University, Netherlands, since September 2018. He is the director and PI of Robotic and Tactile intelligence Group Lab (RoboTac).
He enjoys research at the intersection of Robotics, Interactive Perception, Machine Learning, and Control applied to problems in Mobile Robotic, Robotic Grasping and Manipulation, and Human-Robot interaction and collaboration.
He is a PI of several European funded research projects, such as PHASTRAC, INTUITIVE (Tactile User Interface), iNavigate (Brain Inspired Perception for Navigation and Mobility), SmartNets, and etc.
Formerly, he was a group leader of tactile robotic and postdoctoral research fellow at the Institute for Advanced Studies (IAS), the Technical University of Munich (TUM), Germany from September 2017 till August 2018. He received his Ph.D. degree with the highest distinction (summa cum laude) in robotics focusing on tactile perception and learning in robotics from TUM in 2017. He was awarded the best European Ph.D. thesis prize in robotics, Georges Giralt Ph.D. Award (finalist).
Mohsen Kaboli is the inventor/co-inventor of approximately 20 patents and author of approximately 40 Journals, proceedings, and editorials. His research over the past 10 years has been bridging several research domains, the most important ones being tactile intelligence, AI, and robotics. This also been acknowledged by the IEEE, when being named IEEE Senior Member in 2018 for his“contributions in AI and Robotics.