Category: Research

Control of Micro Aerial Vehicles under Aerodynamic and Physical Contact Interactions

Overview The goal of this project is to make quadrotors and other similar small-scale flying rotorcraft safer and easier to fly. Both recreational and commercial use of these vehicles has recently surged in popularity. However, safety concerns about potentially damaging collisions limit their deployment near people or in close formation, and the current state of […]

Distributed semantic processing in camera networks

Overview In many applications, sensor networks can be used to monitor large geographical regions. This typically produces large quantities of data that need to be associated, summarized and classified in order to arrive to a semantically meaningful descriptions of the phenomena being monitored. The long-term guiding vision of this project is a distributed network that […]

Vision-based formation control

The goal of formation control is to move a group of agents in order to achieve and maintain a set of desired relative positions. This problem has a long history, and latest trends emphasize the use of vision-based solution. In this setting, the measurement of the relative direction (i.e., bearing) between two agents can be […]

Distributed localization algorithms

Imagine a wireless camera network, where each camera has a piece of local information, e.g., the pose of the object from a specific viewpoint or the relative poses with respect to the neighboring cameras. It is natural to look for distributed algorithms which merge all these local measurements into a single, globally consistent estimate. I […]

Consensus algorithms on Riemannian manifolds

Given a group of agents which move in Euclidean space and communicate according to a given communication graph, standard consensus algorithms provide a protocol which, as time passes, brings all the agents to a common location. The key aspect here is that only local communications are used. These algorithms, however, do not apply when the […]

Distributed optimization on Riemannian manifolds

I worked on distributed optimization problems involving variables lying on non-linear spaces (that is, Riemannian manifolds) using extensions of gradient descent algorithms with fixed step size. I developed novel theoretical tools which significantly broadened the state of the art for determining sufficient conditions for global behaviors (algorithm convergence) using only local information. These tools have […]

Motion segmentation

My initial research included the comparison of different algorithms for segmenting multiple moving objects in a monocular video.  For this purpose, I created the Hopkins 155 dataset, which, since its introduction, has been used in over 150 scholarly articles and is a de-facto standard benchmark in this field. The following is a frame from the […]