Supernumerary Robotic Fingers as a Therapeutic Device for Hemiparetic Patients

Patients with hemiparesis often have limited functionality in the left or right hand. The standard therapeutic approach requires the patient to attempt to make use of the weak hand even though it is not functionally capable, which can result in feelings of frustration. Furthermore, hemiparetic patients also face challenges in completing many bimanual tasks, for example walker manipulation, that are critical to patients’ independence and quality of life. A prototype therapeutic device with two supernumerary robotic fingers was used to determine if robotic fingers could functionally assist a human in the performance of bimanual tasks by observing the pose of the healthy hand. Specific focus was placed on the identification of a straightforward control routine which would allow a patient to carry out simple manipulation tasks with some intermittent input from a therapist. Part of this routine involved allowing a patient to switch between active and inactive monitoring of hand position, resulting in additional manipulation capabilities. The prototype successfully enabled a test subject to complete various bimanual tasks using the robotic fingers in place of normal hand motions. From these results, it is clear that the device could allow a hemiparetic patient to complete tasks which would previously have been impossible to perform

A robotic hand that utilizes ergonomic evaluation as feedback to improve human robot collaboration in soldering applications

Thesis: S.B., Massachusetts Institute of Technology, Department of Mechanical Engineering, 2016.Cataloged from PDF version of thesis.Includes bibliographical references (pages 49-50).People never seem to have enough hands. There are many tools that aim to address this challenge, ranging from the ubiquitous benchtop vise to the "helping hands" commonly used for soldering. However, these tools do not measure up to their human counterparts. They cannot adjust the position or orientation of the workpiece to suit a particular task which can cause workers to maintain unhealthy postures that are detrimental to their long-term health. This thesis addresses this shortcoming with a robotic arm that utilizes a gripper to grasp and hold a workpiece during a soldering task. The robot uses a Microsoft Kinect sensor to continuously analyze the posture of the human worker and calculate a score based on the RULA (Rapid Upper Limb Assessment), an objective measure used in the ergonomics field to evaluate ergonomic working postures. The robot adjusts the workpiece in order to optimize the RULA score using an adaptive simulated annealing algorithm to balance the exploration and exploitation phases of the optimization process. Initial testing indicates that the robot can consistently find positions which improve the RULA ranking by 24.6% of the measured range. This project demonstrates that human robot collaboration can be improved by utilizing sensors to evaluate the needs of a human partner and adjust the robot behavior accordingly.by Moses Teddy Ort.S.B

Autonomous navigation in rural environments without detailed prior maps

Thesis: S.M., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, February, 2020Cataloged from PDF version of thesis.Includes bibliographical references (pages 69-73).Most autonomous vehicle systems currently rely on high-definition prior maps in order to localize and navigate in their environment. In this work, we present MapLite: a one-click autonomous navigation system capable of piloting a vehicle to an arbitrary desired destination point given only a sparse publicly available topometric map (from OpenStreetMap). The onboard sensors are used to segment the road region and register the topometric map in order to fuse the high-level navigation goals with a variational path planner in the vehicle frame. This enables the system to plan trajectories that correctly navigate road intersections without the use of an external localization system such as GPS or a detailed prior map. Since the topometric maps already exist for the vast majority of roads, this solution greatly increases the geographical scope for autonomous mobility solutions. We implement MapLite on a full-scale autonomous vehicle and exhaustively test it on over 15km of real-world driving including over 100 autonomous intersection traversals. We further extend these results through simulated testing to validate the system on complex road junction topologies such as traffic circles.by Teddy Ort.S.M.S.M. Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Scienc

Probabilistic Risk Metrics for Navigating Occluded Intersections

Among traffic accidents in the USA, 23% of fatal and 32% of non-fatal incidents occurred at intersections. For driver assistance systems, intersection navigation remains a difficult problem that is critically important to increasing driver safety. In this letter, we examine how to navigate an unsignalized intersection safely under occlusions and faulty perception. We propose a real-time, probabilistic, risk assessment for parallel autonomy control applications for occluded intersection scenarios. The algorithms are implemented on real hardware and are deployed in a variety of turning and merging topologies. We show phenomena that establish go/no-go decisions, augment acceleration through an intersection and encourage nudging behaviors toward intersections.United States. Office of Naval Research (Grant N00014-18-1-2830

MapLite: Autonomous Intersection Navigation Without a Detailed Prior Map

In this work, we present MapLite: a one-click autonomous navigation system capable of piloting a vehicle to an arbitrary desired destination point given only a sparse publicly available topometric map (from OpenStreetMap). The onboard sensors are used to segment the road region and register the topometric map in order to fuse the high-level navigation goals with a variational path planner in the vehicle frame. This enables the system to plan trajectories that correctly navigate road intersections without the use of an external localization system such as GPS or a detailed prior map. Since the topometric maps already exist for the vast majority of roads, this solution greatly increases the geographical scope for autonomous mobility solutions. We implement MapLite on a full-scale autonomous vehicle and exhaustively test it on over 15 km of road including over 100 autonomous intersection traversals. We further extend these results through simulated testing to validate the system on complex road junction topologies such as traffic circles

Rapidly scalable mechanical ventilator for the COVID-19 pandemic

The SARS-CoV-2 pandemic is straining healthcare systems worldwide, and a global ventilator shortage is fueling the dire situation. As a response, the MIT E-Vent Team (S1) manufactured a scalable ventilator prototype for mass production and demonstrated basic clinical feasibility