This project aims to compute quantitative behavioral measures related todepression severity from facial expression, body gestures, and vocalprosody in clinical interviews.
The goal of this project is to develop methods to accurately model wall surfaces even when they are partially occluded and contain numerous openings, such as windows and doorways.
We are developing novel dynamically-stable rolling machine and walking machine research platforms to study interactions with people and operating in normal home and workplace environments.
“Extrinsic Dexterity” is a way to get dexterous manipulation with a very simple hand, by coordinating finger motion with arm motion. The more common approach is to depend entirely on the fingers of the hand, which requires at least three fingers and at least nine motors. We have demonstrated Extrinsic Dexterity using the single motor of the MLab Hand, coordinated with the motions of the arm.
Use of machine learning techniques to predict the injury pattern of the Anterior Cruciate Ligament (ACL) using non-invasive methods.
Cyber-Physical Systems (CPS) encompass a large variety of systems including example future energy systems (e.g. smart grid), homeland security and emergency response, smart medical technologies, smart cars and air transportation. The goal of this project is to develop cognitively-based analytic models of human operators so that they can be integrated with models of the physical/robotic system so that the whole mixed human-CPS system can be formally verified.
We are developing tools and techniques to support formal verification of autonomous systems.
shorten MEMS development cycle
We are part of a $30 million international competition to safely land a robot on the surface of the Moon, travel 500 meters over the lunar surface, and send images and data back to the Earth.
In this project, we are developing mapping and localization methods that combine aerial imagery from satellite and aerial platforms with maps and perception from ground-based robots to produce integrated maps even when GPS is unavailable.
We have developed a novel and relatively simple method for magnifying forces perceived by an operator using a tool. A sensor measures the force between the tip of a tool and its handle held by the operator’s fingers.
A miniature mobile robot for minimally invasive therapy on the beating heart through a single percutaneous incision.
In this project we develop the trajectory planning system for an autonomous helicopter. The helicopter is used for cargo delivery. To read more about the trajectory planning system see the following publications.
We developed and tested a prototype based on an innovative approach of a highly articulated robotic probe.
Machine learning algorithms to detect hot flashes in women using physiological measures.
The human-robot interaction project explores aspects of social interaction between people and robots, in particular how robots should be designed to provide people with appropriate interactions.
We are developing inexpensive robotic approaches towards hydroponic growing, which can increase overall crop yield.
We have developed a new image-based guidance system for microsurgery using optical coherence tomography (OCT), which presents a continuously updated virtual image in its correct location inside the scanned tissue. OCT provides real-time, 6-micron resolution images at video rates within a 2-6 mm axial range in soft or transparent tissue, and is therefore suitable for guidance to various targets in the eye.
Our goal is to fly indoors in degraded visual environments to localize people and fire. We are developing accurate real-time localization and control to be able to fly in these challenging conditions.
Tracking multiple people in indoor environments with the connectivity of Bluetooth devices.