IER Seminar Series: Dr. Monroe Kennedy III

*This event is virtual only*

Zoom: https://northeastern.zoom.us/j/98344781352

Title: DenseTact: Calibrated Optical Tactile Sensing for the Next Generation of Robotic Manipulation

Abstract:

Robotic dexterity stands to be the key challenge to making collaborative robots ubiquitous in the home and industry environments, particularly those that require adaptive systems. The last few decades have produced many solutions in this space that include mechanical transducers (pressure sensors) that while effective usually suffer limitations of the resolution, cross-talk, and limited multi-modal sensing at every point. There are passive, soft sensors that through high friction and form-closure envelope items to be manipulated for stable grasps, and while often effective at securing a grasp, such sensors generally do not provide the dexterity needed to re-grasp, perform finger gaiting or truly quantify the stability of a grasp beyond basic immobilization observed through action. Finally, optical tactile sensors have presented many new avenues for research, with leading designs being GelSight and GelSlim for surface reconstruction and force estimation. While optical tactile sensors stand to be robotics best answer so far to sensing sensitivity that approaches anthropomorphic performance, there is still a noticeable gap in robotics research when it comes to performing manipulation tasks, with end-to-end solutions struggling to extend to new complex manipulation tasks without significant (and often unscalable) training.

In this talk, I will present DenseTact an optical tactile sensor that provides calibrated surface reconstruction and forces for a single fingertip. This calibrated, anthropomorphically inspired fingertip design will allow for modularization of the grasping process and open new avenues of research in robotic manipulation towards collaborative robotic applications.

Bio:

Monroe Kennedy III is an assistant professor in Mechanical Engineering and courtesy of Computer Science at Stanford University. Prof. Kennedy is the recipient of the NSF Faculty Early Career Award. He leads the Assistive Robotics and Manipulation laboratory (arm.stanford.edu), which develops collaborative robotic assistants by focusing on combining modeling and control techniques together with machine learning tools. Together, these techniques will improve robotic performance for tasks that are highly dynamic, require dexterity, have considerable complexity, and require human-robot collaboration. He received his Ph.D. in Mechanical Engineering and Applied Mechanics and Masters in Robotics at the University of Pennsylvania and was a member of the GRASP Lab.