Organizational Unit:

Institute for Robotics and Intelligent Machines (IRIM)

Permanent Link

https://hdl.handle.net/1853/70657

Includes Organization(s)

Organizational Unit

Biorobotics and Human Modeling Lab

Organizational Unit

Humanoid Robotics Laboratory

Full item page

Publication Search Results

Now showing 1 - 10 of 50

Robust 3D Visual Tracking Using Particle Filtering on the Special Euclidean Group: A Combined Approach of Keypoint and Edge Features

(Georgia Institute of Technology, 2012-03-07) Choi, Changhyun ; Christensen, Henrik I.

We present a 3D model-based visual tracking approach using edge and keypoint features in a particle filtering framework. Recently, particle filtering based approaches have been proposed to integrate multiple pose hypotheses and have shown good performance, but most of the work has made an assumption that an initial pose is given. To ameliorate this limitation, we employ keypoint features for initialization of the filter. Given 2D-3D keypoint correspondences, we randomly choose a set of minimum correspondences to calculate a set of possible pose hypotheses. Based on the inlier ratio of correspondences, the set of poses are drawn to initialize particles. After the initialization, edge points are employed to estimate inter-frame motions. While we follow a standard edge-based tracking, we perform a refinement process to improve the edge correspondences between sampled model edge points and image edge points. For better tracking performance, we employ a first order autoregressive state dynamics, which propagates particles more effectively than Gaussian random walk models. The proposed system re-initializes particles by itself when the tracked object goes out of the field of view or is occluded. The robustness and accuracy of our approach is demonstrated using comparative experiments on synthetic and real image sequences.
Medical and health-care robotics

(Georgia Institute of Technology, 2010-09) Okamura, Allison M. ; Mataric, Maja J. ; Christensen, Henrik I.

The aim of this article is to propose some of the most important capabilities and technical achievements of medical and health-care robotics needed to improve human health and well-being. The paper describes application areas, societal drivers, motivating scenarios, desired system capabilities, and fundamental research areas that should be considered in the design of medical and health-care robots.
Detecting region transitions for human-augmented mapping

(Georgia Institute of Technology, 2010-08) Christensen, Henrik I. ; Topp, Elin A.

In this paper, we describe a concise method for the feature-based representation of regions in an indoor environment and show how it can also be applied for door-passage-independent detection of transitions between regions to improve communication with a human user.
Applying domain knowledge to slam using virtual measurements

(Georgia Institute of Technology, 2010-05) Trevor, Alexander J. B. ; Rogers, John G. ; Nieto-Granda, Carlos ; Christensen, Henrik I.

Simultaneous Localization and Mapping (SLAM) aims to estimate the maximum likelihood map and robot pose based on a robot’s control and sensor measurements. In structured environments, such as human environments, we might have additional domain knowledge that could be applied to produce higher quality mapping results.We present a method for using virtual measurements, which are measurements between two features in our map. To demonstrate this, we present a system that uses such virtual measurements to relate visually detected points to walls detected with a laser scanner.
Real-time 3d model-based tracking using edge and keypoint features for robotic manipulation

(Georgia Institute of Technology, 2010-05) Choi, Changhyun ; Christensen, Henrik I.

We propose a combined approach for 3D real-time object recognition and tracking, which is directly applicable to robotic manipulation. We use keypoints features for the initial pose estimation. This pose estimate serves as an initial estimate for edge-based tracking. The combination of these two complementary methods provides an efficient and robust tracking solution. The main contributions of this paper includes: 1) While most of the RAPiD style tracking methods have used simplified CAD models or at least manually well designed models, our system can handle any form of polygon mesh model. To achieve the generality of object shapes, salient edges are automatically identified during an offline stage. Dull edges usually invisible in images are maintained as well for the cases when they constitute the object boundaries. 2) Our system provides a fully automatic recognition and tracking solution, unlike most of the previous edge-based tracking that require a manual pose initialization scheme. Since the edge-based tracking sometimes drift because of edge ambiguity, the proposed system monitors the tracking results and occasionally re-initialize when the tracking results are inconsistent. Experimental results demonstrate our system's efficiency as well as robustness.
Domestic robot ecology - an initial framework to unpack long-term acceptance of robots at home

(Georgia Institute of Technology, 2010) Sung, Ja-Young ; Grinter, Rebecca E. ; Christensen, Henrik I.

It has been recognized that long-term effects exist in the interaction with robotic technologies. Despite this recognition, we still know little about how the temporal effects are associated with domestic robots. To bridge this gap, we undertook a long-term field study. We distributed Roomba vacuuming robots to 30 households, and observed the use over six months. During this study, which spans over 149 home visits, we identified how householders accepted robots as a part of the households via four temporal stages of pre-adoption, adoption, adaptation, and use/retention. With these findings, we took the first step toward establishing a framework, Domestic Robot Ecology (DRE). It shows a holistic view on the relationships that robots shape in the home. Further, it articulates how those relationships change over time. We suggest that DRE can become a useful tool to help design toward long-term acceptance of robotic technologies in the home.
Computational visual attention systems and their cognitive foundation: A survey

(Georgia Institute of Technology, 2010) Frintrop, Simone ; Rome, Erich ; Christensen, Henrik I.

Based on concepts of the human visual system, computational visual attention systems aim to detect regions of interest in images. Psychologists, neurobiologists, and computer scientists have investigated visual attention thoroughly during the last decades and profited considerably from each other. However, the interdisciplinarity of the topic holds not only benefits but also difficulties: concepts of other fields are usually hard to access due to differences in vocabulary and lack of knowledge of the relevant literature. This paper aims to bridge this gap and bring together concepts and ideas from the different research areas. It provides an extensive survey of the grounding psychological and biological research on visual attention as well as the current state of the art of computational systems. Furthermore, it presents a broad range of applications of computational attention systems in fields like computer vision, cognitive systems and mobile robotics. We conclude with a discussion on the limitations and open questions in the field.
Constructing a high-performance robot from commercially available parts

(Georgia Institute of Technology, 2009-12) Smith, Christian ; Christensen, Henrik I.

Robot manipulators were the topic of this article. A large number of robot manipulators have been designed over the last half century, and several of these have become standard platforms for R&D efforts. The most widely used is the Unimate PUMA 560 series. Recently, there have been attempts to utilize standard platforms, as exemplified by the learning applied to ground robots (LAGRs) program organized by Defense Advanced Research Projects Agency (DARPA). The RobotCub project has also made a few robots available to the research community. As actuation systems have become more powerful and miniaturized, it has become possible to build dynamical robot systems to perform dynamic tasks.However, for research work, it is often a challenge to get access to a high-performance robot, which is also available to other researchers. In many respects, robotics has lacked standard systems based upon which comparative research could be performed. Too much research is performed on a basis that cannotbe replicated, reproduced, or reused. For basic manipulation, there has until recently been limited access to light weight manipulators with good dynamics.In this article, it describe the design of a high-performance robot manipulator that is built from components off the shelf to allow easy replication. In addition, it was designed to have enough dynamics to allow ball catching, which in reality implies that the system has adequate dynamics for most tasks.
Visual Place Categorization: Problem, Dataset, and Algorithm

(Georgia Institute of Technology, 2009-10) Wu, Jianxin ; Rehg, James M. ; Christensen, Henrik I.

In this paper we describe the problem of Visual Place Categorization (VPC) for mobile robotics, which involves predicting the semantic category of a place from image measurements acquired from an autonomous platform. For example, a robot in an unfamiliar home environment should be able to recognize the functionality of the rooms it visits, such as kitchen, living room, etc. We describe an approach to VPC based on sequential processing of images acquired with a conventional video camera.We identify two key challenges: Dealing with non-characteristic views and integrating restricted-FOV imagery into a holistic prediction. We present a solution to VPC based upon a recently-developed visual feature known as CENTRIST (CENsus TRansform hISTogram). We describe a new dataset for VPC which we have recently collected and are making publicly available. We believe this is the first significant, realistic dataset for the VPC problem. It contains the interiors of six different homes with ground truth labels. We use this dataset to validate our solution approach, achieving promising results.
Wii-mote robot control using human motion models

(Georgia Institute of Technology, 2009-10) Smith, Christian ; Christensen, Henrik I.

As mass-market video game controllers have become more advanced, there has been a recent increase in interest for using these as intuitive and inexpensive control devices. In this paper we examine position control for a robot using a wiimote game controller. We show that human motion models can be used to achieve better precision than traditional tracking approaches, sufficient for simpler tasks. We also present an experiment that shows that very intuitive control can be achieved, as novice subjects can control a robot arm through simple tasks after just a few minutes of practice and minimal instructions.