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Events for June

  • Dr. Andrea Gasparri, Multi-Robot Systems: A Control Perspective- Tutorial Part I

    Dr. Andrea Gasparri,  Multi-Robot Systems: A Control Perspective- Tutorial Part I

    Tue, Jun 04, 2013 @ 11:00 AM - 12:30 PM

    Ming Hsieh Department of Electrical and Computer Engineering

    University Calendar


    Research Talk by Dr. Andrea Gasparri, Assistant Professor, Engineering Department, Roma Tre University, Italy

    Title: Multi-Robot Systems: A Control Perspective

    Abstract: Multi-Robot Systems represent an important research field with a wide variety of topics to be addressed. In recent years a great effort has been made by the research community towards the development of decentralized techniques to provide an adequate level of robustness and flexibility to these systems. This tutorial will provide first a general overview of this research area, focusing on the most important design aspects of a multi-robot system, e.g. control and communication architecture, and illustrating the most important research problems. Then, it will focus on the control aspects of the distributed cooperation problem. In that context, the consensus problem will be first reviewed as a starting point towards the investigation of more refined techniques to achieve spatial aggregation between the robotic units. Furthermore, the connectivity maintenance problem will be introduced, a taxonomy of the approaches available at the state of the art will be derived and some relevant techniques will be described more in detail. Finally, relevant applications in the context of multi-robot systems which rely on the distributed coordination techniques previously introduced will be highlighted.

    Biography: Andrea Gasparri received the Graduate degree (cum laude) in computer science in 2004 and the Ph.D. degree in computer science and automation in 2008, both from the University of Rome Roma Tre, Rome, Italy. He is currently an Assistant Professor for the Engineering Department, University of Rome Roma Tre. His current research interests include mobile robotics, sensor networks, and, more generally, networked multi-agent systems.

    Dr. Gasparri is a young expert with rapidly growing recognition in the emerging area of distributed networked robotics, a field at the intersection of control, robotics, and networking that is currently gaining in importance. Dr. Gasparri will be visiting USC from May 21 to June 30, 2013.

    Organizer(s): Bhaskar Krishnamachari and Gaurav Sukhatme
    Sponsored by the Ming Hsieh Institute
    For more information: http://mhi.usc.edu/2013/05/01/dr-andrea-gasparri/

    More Information: Flyer for talks.pdf

    Location: 248

    Audiences: Everyone Is Invited

    Contact: Danielle Hamra

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  • PhD Defense - Furqan Khan

    Thu, Jun 06, 2013 @ 02:00 PM - 04:00 PM

    Thomas Lord Department of Computer Science

    University Calendar


    Date: June 6, 2013
    Time: 2:00pm
    Location: PHE 223

    Thesis by:
    Furqan M Khan

    Committee Members:
    Ram Nevatia (Chair)
    Gerard Medioni
    Keith Jenkins (Outside Member)

    Abstract:
    With cameras getting smaller, better and cheaper, the amount of videos produced these days has increased exponentially. Although not comprehensive by any means, the fact that about 35 hours of video is uploaded to YouTube every minute is indicative of the amount of data that is being generated. This is in addition to the videos recorded for surveillance by grocery stores and by security agencies at airports, train stations and streets. Whereas analysis of the video data is the core reason for surveillance data collection, services such as YouTube can also use video analysis to improve search and indexing tasks. However, due to extremely large amount of data generation, human video analysis is not feasible; therefore, development of methods which can automatically perform the intelligent task of visual understanding, specifically human activity recognition, has seen a lot of interest in past couple of decades. Such capability is also desired to improve human computer interaction. However, the associated problem of activity description, i.e., information about actor, location and object of information, has not got much attention despite its importance for surveillance and indexing tasks. In this thesis, I propose methods for automated action analysis, i.e., recognition and description of human activities in videos.
    The task of activity recognition is seemingly easily performed by humans but it is very difficult for machines. The key challenge lies in modeling of human actions and representation of transformation of visual data with time. This thesis contributes to provide possible solutions related to development of action models to facilitate action description which are general enough to capture large variations in an action class while allowing for robust discrimination of different action classes and corresponding inference mechanisms. I model actions as a composition of several primitive events and use graphical models to evaluate consistency of action models with video input. In the first part of the thesis, I use low-level features to capture the transformation of spatiotemporal data during the primitive event. In the second part, to facilitate description of activities, such as identification of actor and object of interaction, I decompose actions using high-level constructs, actors and objects. Primitive components represent properties of actors and their relationships with objects of interaction. In the end, I represent actions as transformation of actor's limbs (human pose) over time and decompose actions using key poses. I infer human pose, object of interaction and the action for each actor jointly using a dynamic Bayesian Network.

    This thesis furthers research on relatively ignored but more comprehensive problem of action analysis, i.e., action recognition with the associated problem of description. To support the thesis, I evaluated the presented algorithms on publicly available datasets. The performance metrics highlight effectiveness of my algorithms on datasets which offer large variations in execution, viewpoint, actors, illuminations, etc.

    Location: Charles Lee Powell Hall (PHE) - 223

    Audiences: Everyone Is Invited

    Contact: Lizsl De Leon

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  • Dr. Andrea Gasparri, Multi-Robot Systems: A Control Perspective II

    Dr. Andrea Gasparri, Multi-Robot Systems: A Control Perspective II

    Fri, Jun 07, 2013 @ 11:00 AM - 12:30 PM

    Ming Hsieh Department of Electrical and Computer Engineering

    University Calendar


    Research Talk by Dr. Andrea Gasparri, Assistant Professor, Engineering Department, Roma Tre University, Italy

    Title: Multi-Robot Systems: A Control Perspective II

    Abstract: Multi-Robot Systems represent an important research field with a wide variety of topics to be addressed. In recent years a great effort has been made by the research community towards the development of decentralized techniques to provide an adequate level of robustness and flexibility to these systems. This tutorial will provide first a general overview of this research area, focusing on the most important design aspects of a multi-robot system, e.g. control and communication architecture, and illustrating the most important research problems. Then, it will focus on the control aspects of the distributed cooperation problem. In that context, the consensus problem will be first reviewed as a starting point towards the investigation of more refined techniques to achieve spatial aggregation between the robotic units. Furthermore, the connectivity maintenance problem will be introduced, a taxonomy of the approaches available at the state of the art will be derived and some relevant techniques will be described more in detail. Finally, relevant applications in the context of multi-robot systems which rely on the distributed coordination techniques previously introduced will be highlighted.

    Biography: Andrea Gasparri received the Graduate degree (cum laude) in computer science in 2004 and the Ph.D. degree in computer science and automation in 2008, both from the University of Rome Roma Tre, Rome, Italy. He is currently an Assistant Professor for the Engineering Department, University of Rome Roma Tre. His current research interests include mobile robotics, sensor networks, and, more generally, networked multi-agent systems.

    Dr. Gasparri is a young expert with rapidly growing recognition in the emerging area of distributed networked robotics, a field at the intersection of control, robotics, and networking that is currently gaining in importance. Dr. Gasparri will be visiting USC from May 21 to June 30, 2013.

    Organizer(s): Bhaskar Krishnamachari and Gaurav Sukhatme
    Sponsored by the Ming Hsieh Institute
    For more information: http://mhi.usc.edu/2013/05/01/dr-andrea-gasparri/

    More Information: Flyer for talks.pdf

    Location: EEB 248

    Audiences: Everyone Is Invited

    Contact: Danielle Hamra

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  • Dr. Andrea Gasparri, Swarm Aggregation Algorithms for Multi-Robot Systems

    Dr. Andrea Gasparri, Swarm Aggregation Algorithms for Multi-Robot Systems

    Tue, Jun 11, 2013 @ 11:00 AM - 12:00 PM

    Ming Hsieh Department of Electrical and Computer Engineering

    University Calendar


    Research Talk by Dr. Andrea Gasparri, Assistant Professor, Engineering Department, Roma Tre University, Italy

    Title: Swarm Aggregation Algorithms for Multi-Robot Systems

    Abstract: In this work, a novel decentralized swarm aggregation algorithm for multi-robot systems is proposed. In this framework, the interaction among robots is limited to their visibility neighborhood, i.e., robots that are within the visibility range of each other. Furthermore, to better comply with the hardware/software limitations of mobile robotic platforms, robots actuators are assumed to be saturated. An enhanced version of the proposed control law is also discussed. Improvements mainly concerns two aspects: i) the actuator saturation can be asymmetric with respect to the forward and backward velocity to better comply with the hardware/software specifications, and ii) the obstacle avoidance algorithm can be more easily integrated within the local control law of each robot ensuring a safer navigation in an environment filled with obstacles. A theoretical characterization of the main properties of the proposed swarm aggregation algorithms is provided. Simulations have been carried out to validate the theoretical results. Furthermore, experiments have been performed with a team of low-cost mobile robots to demonstrate the effectiveness of the proposed approach in a real-world environment.

    Biography: Andrea Gasparri received the Graduate degree (cum laude) in computer science in 2004 and the Ph.D. degree in computer science and automation in 2008, both from the University of Rome Roma Tre, Rome, Italy. He is currently an Assistant Professor for the Engineering Department, University of Rome Roma Tre. His current research interests include mobile robotics, sensor networks, and, more generally, networked multi-agent systems.

    Dr. Gasparri is a young expert with rapidly growing recognition in the emerging area of distributed networked robotics, a field at the intersection of control, robotics, and networking that is currently gaining in importance. Dr. Gasparri will be visiting USC from May 21 to June 30, 2013.

    Organizer(s): Bhaskar Krishnamachari and Gaurav Sukhatme
    Sponsored by the Ming Hsieh Institute
    For more information: http://mhi.usc.edu/2013/05/01/dr-andrea-gasparri

    More Information: Flyer for talks.pdf

    Location: EEB 248

    Audiences: Everyone Is Invited

    Contact: Danielle Hamra

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  • EE Alumni Reception (San Jose)

    EE Alumni Reception (San Jose)

    Thu, Jun 13, 2013 @ 05:00 PM - 08:00 PM

    Ming Hsieh Department of Electrical and Computer Engineering

    University Calendar


    The Electrical Engineering Department is the Viterbi School’s largest, and one of the largest of its kind in the nation. The Ming Hsieh Institute (MHI) was established to complement and enhance the department’s academic and research programs and promote emerging fields within electrical engineering. Staying connected with electrical engineering alums is one of our main goals to continue enhancing innovation and excellence.

    The reception is a casual networking event so attendees can re-connect with former classmates and meet local alums with the possibility for future collaboration. There will be good conversation about the latest alumni accomplishments as well as exciting activities and research happening in the department. Cocktail reception refreshments will be provided.

    Tickets: $25 per person (tickets must be purchased by 6/10)
    BUY TICKETS

    View attendees: http://mhi.usc.edu/ee-alumni-reception-bay-area/

    Location: Fairmont San Jose

    Audiences: EE Bay Area Alumni

    Contact: Danielle Hamra

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  • PhD Defense - Houtan Shirani-Mehr

    Fri, Jun 14, 2013 @ 11:00 AM - 01:00 PM

    Thomas Lord Department of Computer Science

    University Calendar


    PhD Candidate: Houtan Shirani-Mehr

    Title: Efficient Reachability Query Evaluation in Large Spatiotemporal Contact Networks

    Committee:
    Cyrus Shahabi (Chairman)
    Shrikanth Narayanan
    C.-C. Jay Kuo

    Time: June 14, 11am-1pm
    Location: PHE 333

    Abstract:
    In many application scenarios, an item, such as a message, a piece of sensitive information, contagious virus or a malicious malware, passes between two objects, such as moving vehicles, individuals or cell phone devices, when the objects are sufficiently close (i.e., when they are, so-called, in contact), and some application specific "constraints" are satisfied. An example of constraint in the transmission of a malware is that it takes some time such that the malware is activated on a cell phone and then it can be transmitted to another one via Bluetooth. As another example for constraint, a message passes between two vehicles with a probability which depends on various conditions such as the distance between the vehicles. In such applications, once an item is initiated, it can penetrate the object population through the evolving network of contacts among objects, termed "contact network''. A reachability query evaluates whether two objects are "reachable'' through the contact network. In this dissertation, we define and study reachability query in large (i.e., disk resident) contact datasets which verifies whether two objects are “reachable” through the contact network represented by such contact datasets. The main characteristics of our problem are the large scale of the contact dataset as well as the dynamism of the network which models the contact dataset. This underlying network evolves over the time period during which the contact dataset is constructed as the objects are moving in the environment and subsequently new contacts appear and old contacts disappear over time.

    In this dissertation, due to the complexity of the general problem, we first simplify the problem by focusing on reachability in contact datasets with no-constraints. With such contact datasets, an item passes between two objects when they are close enough. We propose two contact dataset indexes, termed ReachGrid and ReachGraph, for efficient reachability query processing. With ReachGrid, at the query time only a small necessary portion of the contact dataset is constructed and traversed. With ReachGraph, we precompute and leverage reachability at different scales for efficient query processing. We optimize the disk placement of both indexes for efficient query processing.

    Afterward, we extend ReachGrid and ReachGraph for contact networks with constraints. To this end, as a case study we focus on a specific type of constraint, i.e., the latency constraint, and adopt ReachGraph and ReachGrid for efficient reachability query processing.
    Furthermore, we discuss how to generalize ReachGraph and ReachGrid for contact networks with general constraints based on the insights we obtain from focusing on contact networks with latency.

    Location: Charles Lee Powell Hall (PHE) - 333

    Audiences: Everyone Is Invited

    Contact: Lizsl De Leon

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