(Author information and Acknowledgments temp. removed!)
Simultaneous Localization and Mapping (SLAM) using an incremental approach based on range image registration with a variant of the Iterative Closest Point (ICP) algorithm by Besl and McKay. The resulting sparse point map models the 3rd floor of the MIT CSAIL building. The data set was recorded by Cyrill Stachniss (University of Freiburg).

TechCrunch Sessions: Robotics is a single-day event designed to facilitate in-depth conversation and networking with the technologists, researchers and students of the robotics community as well as the founders and investors bringing innovation to the masses.

Some scenes of researchers working at MIT in the early days of computer science and artificial intelligence.

Team MIT, led by Russ Tedrake, competed in the 2015 DARPA Robotics Challenge finals on June 5-6 in Pomona, CA. Robots had to complete a course of eight tasks in under an hour. Team MIT completed seven of the eight tasks in 50:25.

Video: Tom Buehler / MIT CSAIL

For more info: http://www.csail.mit.edu/baxter_soft_robotic_gripper

From the paper "Haptic Identification of Objects Using a Soft Robotic Gripper," published in the proceedings of IROS 2015.

This work was done in the Distributed Robotics Laboratory at MIT with support from The Boeing Company and the National Science Foundation, grant numbers NSF IIS1226883, and NSF CCF1138967. We are grateful for this support.

We extract heart rate and beat lengths from videos by measuring subtle head motion caused by the Newtonian reaction to the influx of blood at each beat. Our method tracks features on the head and performs principal component analysis (PCA) to decompose their trajectories into a set of component motions. It then chooses the component that best corresponds to heartbeats based on its temporal frequency spectrum. Finally, we analyze the motion projected to this component and identify peaks of the trajectories, which correspond to heartbeats. When evaluated on 18 subjects, our approach reported heart rates nearly identical to an electrocardiogram device. Additionally we were able to capture clinically relevant information about heart rate variability.


Paper: http://people.csail.mit.edu/klbouman/pw/papers_and_presentations/cornercam_iccv2017.pdf
More info: http://news.mit.edu/2017/artificial-intelligence-for-your-blind-spot-mit-csail-cornercameras-1009

For more info: http://news.mit.edu/2015/wireless-x-ray-vision-could-power-virtual-reality-smart-homes-hollywood-1028