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Intelligent Systems

Associated Projects

James Abello Monedero

Humans can help computers find better answers faster

Kostas Bekris

The increasing availability of low-cost, compliant and human-friendly manipulators allows robots, such as Rethink Robotics' Baxter, to be placed in close proximity to human workers. Unlike traditional automation systems, which needed to be kept in cages, these compliant robots can share a common workspace with human workers. A clear benefit of this close proximity is the opportunity for cooperation between a human worker and an assistive robot.

This project focuses on Multi-Robot Path Planning, with the goal of providing a complete and tractable solution to such instances. The current work considers an abstraction of the traditional multi-robot path planning problem that is abstracted as computing non-colliding paths for multiple agents between their start and goal locations on a graph. Such a formulation is known to be NP-complete, indicating that a naive search to solve the problem will have exponential complexity in the number of robots.

Probabilistic roadmap planners utilize an offline phase to build up information about the configuration space (C-space) and solve many practical motion planning problems. Traditionally, many of these planners focus on feasibility and may return paths of low quality; considerably different from the optimal ones, where path quality can be measured in terms of length, clearance, or smoothness. Smoothing can be used to improve some of these measures and algorithms exist that produce roadmaps with paths that are deformable to optimal ones. Hybridization graphs combine multiple solutions into a higher quality one that uses the best portions of each input path. These techniques, however, can be expensive for the online resolution of a query, especially when multiple queries must be answered.

Many state of the art algorithms for motion planning are concerned with asymptotic optimality (variants of PRM* and RRT*).

Mubbasir Kapadia

We develop computational tools to assist end users to create and experience co

Our research aims to develop integrated solutions for full-body character anim

We develop algorithms for multi-agent motion planning in real-time dynamic env

In order to rigorously evaluate and compare crowd models, we have developed to

We develop models for simulating realistic, believable crowds.

Dimitris Metaxas

Facial Expression Recognition

Accurate face tracking and 3D head pose prediction

Organ shape plays an important role in various clinical practices such as segmentation.

Biomedical Image Analysis Projects.

The first video demonstrats detection of a wh-question non-manual marker. Tracked face and head is shown on left, while the right image shows the extracted spatial pyramid features. Red bars indicate detection of the wh non-manual marker, while blue bars indicate that the system detects no wh non-manual marker.

Konstantinos Michmizos

Neurosurgeons have used electrical stimulation since the 60's to locate and distinguish specific brain areas. They soon discovered that stimulation of certain brain nuclei suppresses the symptoms of some neurological disorders. Recent efforts on patient-specific therapeutic approaches revealed the importance of computational methods in guiding deep brain stimulation (DBS), a neuromodulation treatment initially

One of the biggest challenges in neurodevelopmental disorders today is that they remain behaviorally diagnosed disorders. Despite the large amounts of data from the autistic brain and an abundance of experimental evidences for its pathophysiology, no measures robustly depict the observed differences between an autistic and a typically developing brain. Recently, we measured functional connectivity in the somatosensory cortex in typically developing and autistic

The introduction of impedance control in 1985 by Neville Hogan paved the way for a safe, gentle and effective interaction between humans and machines. This interaction is ideal for rehabilitation and is epitomized in the design of manipulanda that pioneered clinical and neurological applications, the most prominent being the MIT-MANUS, developed by Hermano Igo Krebs. Following this line of research, we have recently introduced the MIT's pediatric Anklebot, an adaptive robotic device that provides an “assist-as-needed” therapy and targets ankle movements in children with neurological disorders (Michmizos et al. 2015). Since 2012, the rehabilitation robot has been used successfully in pilot studies in Pediatric Hospitals in the USA and Europe.

Jingjin Yu

This paper introduces a new mobile sensor scheduling problem invol

We study optimal multi-robot path planning on graphs (MPP) over four minimization objectives: the mak

Desheng Zhang

Carpooling has long held the promise of reducing gas consumption by decreasing mileage to deliver co-riders. Although ad hoc carpools already exist in the real world through private arrangements, little research on the topic has been done. In this paper, we present the first systematic work to design, implement, and evaluate a carpool service, called coRide, in a large-scale taxicab network intended to reduce total mileage for less gas consumption.

Under the Smart Cities Initiative from the White House, this project on urban cyber-physical-systems is aimed to address emerging urban mobility challenges by big-data-driven analytics.

Data-driven modeling usually suffers from data sparsity, especially for large-scale modeling for urban phenomena based on single-source urban infrastructure data under fine-grained spatial-temporal contexts.

Real-time human travel pattern modeling is essential to various applications, from mobile networking, to transportation, urban planning and epidemiology.