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

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Publication Search Results

Now showing 1 - 10 of 51

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.
Normalized graph-cuts for large scale visual SLAM

(Georgia Institute of Technology, 2009-10) Rogers, John G. ; Christensen, Henrik I.

Simultaneous Localization and Mapping (SLAM) suffers from a quadratic space and time complexity per update step. Recent advancements have been made in approximating the posterior by forcing the information matrix to remain sparse as well as exact techniques for generating the posterior in the full SLAM solution to both the trajectory and the map. Current approximate techniques for maintaining an online estimate of the map for a robot to use while exploring make capacity-based decisions about when to split into sub-maps. This paper will describe an alternative partitioning strategy for online approximate real-time SLAM which makes use of normalized graph cuts to remove less information from the full map.
Adding diagnostics to intelligent service robots

(Georgia Institute of Technology, 2009-10) Chandrababu, S. ; Christensen, Henrik I.

Robot systems are increasing in complexity. Trying to diagnose a robot that is non-functional or exhibiting suboptimal performance can be a major challenge. A framework for plug-n-play addition of diagnostics to modules in an object oriented software framework is presented. The methods for modeling of system modules, their transition to a Bayesian model and final implementation are described. The methodology is exemplified for a mobile manipulation system and experimental results are presented.
Cognitive vision for efficient scene processign and object categorization in highly cluttered environments

(Georgia Institute of Technology, 2009-10) Choi, Changhyun ; Christensen, Henrik I.

One of the key competencies required in modern robots is finding objects in complex environments. For the last decade, significant progress in computer vision and machine learning literatures has increased the recognition performance of well localized objects. However, the performance of these techniques is still far from human performance, especially in cluttered environments. We believe that the performance gap between robots and humans is due in part to humans' use of an attention system. According to cognitive psychology, the human visual system uses two stages of visual processing to interpret visual input. The first stage is a pre-attentive process perceiving scenes fast and coarsely to select potentially interesting regions. The second stage is a more complex process analyzing the regions hypothesized in the previous stage. These two stages play an important role in enabling efficient use of the limited cognitive resources available. Inspired by this biological fact, we propose a visual attentional object categorization approach for robots that enables object recognition in real environments under a critical time limitation. We quantitatively evaluate the performance for recognition of objects in highly cluttered scenes without significant loss of detection rates across several experimental settings.
A minimum jerk predictor for teleoperation with variable time delay

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

In this paper we describe a method for bridging internet time delays in a teleoperation scenario. In the scenario, the sizes of the time delays is not only stochastic, but it is also large compared to the task execution time. The method proposed uses minimum jerk motion models to predict the input from the user a time into the future that is equivalent to the one-way communication delay. We present results from a teleoperated ball-catching experiment with real internet delays, where we show that the proposed method makes a significant improvement over traditional methods for teleoperation over intercontinental distances.
Adaptive CPG based coordinated control of healthy and robotics lower limb movement

(Georgia Institute of Technology, 2009-09) Ryu, Jae-Kwan ; Chong, Nak Young ; You, Bum Jae ; Christensen, Henrik I.

This paper proposes an adaptive CPG based controller for a lower limb prosthesis consisting of online trajectory generation and interlimb coordination. The adaptive CPG can produce multidimensional rhythmic patterns and modulate their frequency by tuning relevant parameters in an autonomously way adapting to a changing periodicity of external signals. Also, to increase the stability of the prosthesis, a spring-damper component is attached between the hip and ankle joints, allowing the absorption of impulsive ground reaction forces at landing. We verify the validity of the proposed controller with a simulated humanoid robot through the investigation of the self-coordination between the healthy and robotic legs.
Sketching the future: Assessing user needs for domestic robots

(Georgia Institute of Technology, 2009-09) Sung, Ja-Young ; Grinter, Rebecca E. ; Christensen, Henrik I.

In this paper, we discuss a user-centered vision of future domestic robots based on 48 householders' depiction of their ideal home robots. Through users' creative responses, we aim to identify domestic tasks desired for robotic assistance, and hence guide the design effort to better reflect user needs. Our study results show that householders want domestic robots for tasks including Time-consuming Drudgeries, House-sitting, and Personal Attendance. Further, we present three design lessons we learned to increase householders' acceptance of these robots. The design of domestic robots needs to provide a certain amount of human control, be compatible with the user's domestic environment, and take gender into consideration.
A realistic benchmark for visual indoor place recognition

(Georgia Institute of Technology, 2009-08) Pronobis, A. ; Caputo, B. ; Jensfelt, Patric ; Christensen, Henrik I.

An important competence for a mobile robot system is the ability to localize and perform context interpretation. This is required to perform basic navigation and to facilitate local specific services. Recent advances in vision have made this modality a viable alternative to the traditional range sensors and visual place recognition algorithms emerged as a useful and widely applied tool for obtaining information about robot’s position. Several place recognition methods have been proposed using vision alone or combined with sonar and/or laser. This research calls for standard benchmark datasets for development, evaluation and comparison of solutions. To this end, this paper presents two carefully designed and annotated image databases augmented with an experimental procedure and extensive baseline evaluation. The databases were gathered in an uncontrolled indoor office environment using two mobile robots and a standard camera. The acquisition spanned across a time range of several months and different illumination and weather conditions. Thus, the databases are very well suited for evaluating the robustness of algorithms with respect to a broad range of variations, often occurring in real-world settings. We thoroughly assessed the databases with a purely appearance-based place recognition method based on Support Vector Machines and two types of rich visual features (global and local).