Now showing items 779-798 of 1591

    • Lattice dynamics and melting of a nonequilibrium pattern 

      Goldman, Daniel I.; Shattuck, M. D.; Moon, Sung Joon; Swift, J. B.; Swinney, Harry L. (Georgia Institute of TechnologyAmerican Physical Society, 2003-03-14)
      We present a new description of nonequilibrium square patterns as a harmonically coupled crystal lattice. In a vertically oscillating granular layer, different transverse normal modes of the granular square-lattice pattern ...
    • Lead Me by the Hand: Evaluation of a Direct Physical Interface for Nursing Assistant Robots 

      Chen, Tiffany L.; Kemp, Charles C. (Georgia Institute of TechnologyInstitute of Electrical and Electronics Engineers, 2010-03)
      When a user is in close proximity to a robot, physical contact becomes a potentially valuable channel for communication. People often use direct physical contact to guide a person to a desired location (e.g., leading a ...
    • Leader Selection via the Manipulability of Leader-Follower Networks 

      Kawashima, Hiroaki; Egerstedt, Magnus B. (Georgia Institute of Technology, 2012-06)
      In this paper, we address the problem of selecting leaders in a network by investigating how much instantaneous impact the leaders have on the remaining agents. As a measurement of the influence of leaders’ inputs, we ...
    • A Leader-based Containment Control Strategy for Multiple Unicycles 

      Dimarogonas, Dimos V.; Egerstedt, Magnus B.; Kyriakopoulos, Kostas J. (Georgia Institute of TechnologyInstitute of Electrical and Electronics Engineers, 2006-12)
      In this paper, a leader based containment control strategy for multiple unicycle agents is introduced. Similar results for the single integrator case examined in [7] are derived based on the theory of Partial Difference ...
    • Leader-Based Multi-Agent Coordination Through Hybrid Optimal Control 

      Björkenstam, Staffan; Ji, Meng; Egerstedt, Magnus B.; Martin, Clyde F. (Georgia Institute of TechnologyUniversity of Illinois at Urbana-Champaign, 2006-09)
      The problem of optimally transferring a linear dynamical system between affine varieties arises in a number of applications such as path planning and robot coordination. In this paper, this problem, as well as generalizations ...
    • Learnability for Dynamical Systems 

      O’Flaherty, Rowland; Egerstedt, Magnus (Georgia Institute of Technology, 2014-07)
      This paper takes a step towards defining what it means for a dynamical system, such as a robot, to be able to learn through the notion of learnability. It takes a system-theoretic view to define what learning is and ...
    • Learning about Objects with Human Teachers 

      Thomaz, Andrea L.; Cakmak, Maya (Georgia Institute of TechnologyAssociation for Computing Machinery, 2009)
      A general learning task for a robot in a new environment is to learn about objects and what actions/effects they afford. To approach this, we look at ways that a human partner can intuitively help the robot learn, ...
    • Learning and Inference in Parametric Switching Linear Dynamic Systems 

      Oh, Sang Min; Rehg, James M.; Balch, Tucker; Dellaert, Frank (Georgia Institute of TechnologyInstitute of Electrical and Electronics Engineers, 2005-10)
      We introduce parametric switching linear dynamic systems (P-SLDS) for learning and interpretation of parametrized motion, i.e., motion that exhibits systematic temporal and spatial variations. Our motivating example is ...
    • Learning and Inferring Motion Patterns using Parametric Segmental Switching Linear Dynamic Systems 

      Oh, Sang Min; Rehg, James M.; Balch, Tucker; Dellaert, Frank (Georgia Institute of Technology, 2006)
      Switching Linear Dynamic System (SLDS) models are a popular technique for modeling complex nonlinear dynamic systems. An SLDS has significantly more descriptive power than an HMM by using continuous hidden states. However, ...
    • Learning and Inferring Motion Patterns Using Parametric Segmental Switching Linear Dynamic Systems 

      Oh, Sang Min; Rehg, James M.; Balch, Tucker; Dellaert, Frank (Georgia Institute of TechnologySpringer Berlin / Heidelberg, 2008)
      Switching Linear Dynamic System (SLDS) models are a popular technique for modeling complex nonlinear dynamic systems. An SLDS provides the possibility to describe complex temporal patterns more concisely and accurately ...
    • A Learning Approach to Enable Locomotion of Multiple Robotic Agents Operating in Natural Terrain Environments 

      Howard, Ayanna; Parker, Lonnie T.; Smith, Brian Stephen (Georgia Institute of TechnologyTSI press, 2008)
      This paper presents a methodology that utilizes soft computing approaches to enable locomotion of multiple legged robotic agents operating in natural terrain environments. For individual robotic control, the locomotion ...
    • Learning Approaches Applied to Human-Robot Interaction for Space Missions 

      Remy, Sekou; Howard, Ayanna (Georgia Institute of TechnologyTSI press, 2008)
      Advances in space science and technology have enabled humanity to reach a stage where we are able to send manned and unmanned vehicles to explore nearby planets. However, given key differences between terrestrial and space ...
    • Learning Behavioral Parameterization Using Spatio-Temporal Case-Based Reasoning 

      Arkin, Ronald C.; Kaess, Michael; Likhachev, Maxim (Georgia Institute of Technology, 2001)
      This paper presents an approach to learning an optimal behavioral parameterization in the framework of a Case-Based Reasoning methodology for autonomous navigation tasks. It is based on our previous work on a behavior-based ...
    • Learning Contact Locations for Pushing and Orienting Unknown Objects 

      Hermans, Tucker; Li, Fuxin; Rehg, James M.; Bobick, Aaron F. (Georgia Institute of TechnologyInstitute of Electrical and Electronics Engineers, 2013-10)
      We present a method by which a robot learns to predict effective contact locations for pushing as a function of object shape. The robot performs push experiments at many contact locations on multiple objects and records ...
    • Learning descriptive models of objects and activities from egocentric video 

      Fathi, Alireza (Georgia Institute of Technology, 2013-06-13)
      Recent advances in camera technology have made it possible to build a comfortable, wearable system which can capture the scene in front of the user throughout the day. Products based on this technology, such as GoPro and ...
    • Learning from Examples in Unstructured, Outdoor Environments 

      Sun, J.; Mehta, Tejas R.; Wooden, David; Powers, Matthew; Rehg, J.; Balch, Tucker; Egerstedt, Magnus B. (Georgia Institute of TechnologyWiley Periodicals, Inc., 2006)
      In this paper, we present a multi-pronged approach to the "Learning from Example" problem. In particular, we present a framework for integrating learning into a standard, hybrid navigation strategy, composed of both ...
    • Learning General Optical Flow Subspaces for Egomotion Estimation and Detection of Motion Anomalies 

      Roberts, Richard; Potthast, Christian; Dellaert, Frank (Georgia Institute of TechnologyInstitute of Electrical and Electronics Engineers, 2009)
      This paper deals with estimation of dense optical flow and ego-motion in a generalized imaging system by exploiting probabilistic linear subspace constraints on the flow. We deal with the extended motion of the imaging ...
    • A Learning Methodology for Robotic Manipulation of Deformable Objects 

      Howard, Ayanna M.; Bekey, George A. (Georgia Institute of Technology, 2000-06)
      The majority of manipulation systems are designed with the assumption that the objects being handled are rigid and do not deform when grasped. This paper address the problem of robotic grasping and manipulation of 3- D ...
    • Learning Momentum: Integration and Experimentation 

      Arkin, Ronald C.; Lee, J. Brian (Georgia Institute of Technology, 2000)
      We further study the effects of learning momentum as defined by Clark, Arkin, and Ram[1] on robots, both simulated and real, attempting to traverse obstacle fields in order to reach a goal. Integration of these results ...
    • Learning Momentum: On-Line Performance Enhancement for Reactive Systems 

      Arkin, Ronald C.; Clark, Russell J.; Ram, Ashwin (Georgia Institute of Technology, 1992)
      We describe a reactive robotic control system which incorporates aspects of machine learning to improve the system's ability to successfully navigate in unfamiliar environments. This system overcomes limitations of completely ...