Organizational Unit:
Institute for Robotics and Intelligent Machines (IRIM)

Permanent Link
https://hdl.handle.net/1853/70657
Research Organization Registry ID
Description
Previous Names
Parent Organization
Parent Organization
Includes Organization(s)
Organizational Unit
Organizational Unit
ArchiveSpace Name Record

Filters

2012 - 2015 4
4
4
Reset filters

Settings
Type: Text × search.filters.applied.f.resourcesubtype: Article × search.filters.applied.f.resourcesubtype: Proceedings ×

Publication Search Results

Now showing 1 - 4 of 4
  • Thumbnail Image
    Item
    Incremental Sparse GP Regression for Continuous-time Trajectory Estimation & Mapping
    (Georgia Institute of Technology, 2015-09) Yan, Xinyan ; Indelman, Vadim ; Boots, Byron
    Recent work on simultaneous trajectory estimation and mapping (STEAM) for mobile robots has found success by representing the trajectory as a Gaussian process. Gaussian processes can represent a continuous-time trajectory, elegantly handle asynchronous and sparse measurements, and allow the robot to query the trajectory to recover its estimated position at any time of interest. A major drawback of this approach is that STEAM is formulated as a batch estimation problem. In this paper we provide the critical extensions necessary to transform the existing batch algorithm into an extremely efficient incremental algorithm. In particular, we are able to vastly speed up the solution time through efficient variable reordering and incremental sparse updates, which we believe will greatly increase the practicality of Gaussian process methods for robot mapping and localization. Finally, we demonstrate the approach and its advantages on both synthetic and real datasets.
  • Thumbnail Image
    Item
    Parameter Sensitivity and Boundedness of Robotic Hybrid Periodic Orbits
    (Georgia Institute of Technology, 2015) Kolathaya, Shishir ; Ames, Aaron D.
    Model-based nonlinear controllers like feedback linearization and control Lyapunov functions are highly sensitive to the model parameters of the robot. This paper addresses the problem of realizing these controllers in a particular class of hybrid models-systems with impulse effects-through a parameter sensitivity measure. This measure quantifies the sensitivity of a given model-based controller to parameter uncertainty along a particular trajectory. By using this measure, output boundedness of the controller (computed torque+PD) will be analyzed. Given outputs that characterize the control objectives, i.e., the goal is to drive these outputs to zero, we consider Lyapunov functions obtained from these outputs. The main result of this paper establishes the ultimate boundedness of the output dynamics in terms of this measure via these Lyapunov functions under the assumption of stable hybrid zero dynamics. This is demonstrated in simulation on a 5-DOF underactuated bipedal robot.
  • Thumbnail Image
    Item
    Robustness of Control Barrier Functions for Safety Critical Control
    (Georgia Institute of Technology, 2015) Xu, Xiangru ; Tabuada, Paulo ; Grizzle, Jessy W. ; Ames, Aaron D.
    Barrier functions (also called certificates) have been an important tool for the verification of hybrid systems, and have also played important roles in optimization and multi-objective control. The extension of a barrier function to a controlled system results in a control barrier function. This can be thought of as being analogous to how Sontag extended Lyapunov functions to control Lypaunov functions in order to enable controller synthesis for stabilization tasks. A control barrier function enables controller synthesis for safety requirements specified by forward invariance of a set using a Lyapunov-like condition. This paper develops several important extensions to the notion of a control barrier function. The first involves robustness under perturbations to the vector field defining the system. Input-to-State stability conditions are given that provide for forward invariance, when disturbances are present, of a "relaxation" of set rendered invariant without disturbances. A control barrier function can be combined with a control Lyapunov function in a quadratic program to achieve a control objective subject to safety guarantees. The second result of the paper gives conditions for the control law obtained by solving the quadratic program to be Lipschitz continuous and therefore to gives rise to well-defined solutions of the resulting closed-loop system.
  • Thumbnail Image
    Item
    Learning to Recognize Daily Actions using Gaze
    (Georgia Institute of Technology, 2012-10) Fathi, Alireza ; Li, Yin ; Rehg, James M.
    We present a probabilistic generative model for simultaneously recognizing daily actions and predicting gaze locations in videos recorded from an egocentric camera. We focus on activities requiring eye-hand coordination and model the spatio-temporal relationship between the gaze point, the scene objects, and the action label. Our model captures the fact that the distribution of both visual features and object occurrences in the vicinity of the gaze point is correlated with the verb-object pair describing the action. It explicitly incorporates known properties of gaze behavior from the psychology literature, such as the temporal delay between fixation and manipulation events. We present an inference method that can predict the best sequence of gaze locations and the associated action label from an input sequence of images. We demonstrate improvements in action recognition rates and gaze prediction accuracy relative to state-of-the-art methods, on two new datasets that contain egocentric videos of daily activities and gaze.