The International Journal of Robotics Research

نویسندگان

  • Anastasios I. Mourikis
  • Nikolas Trawny
  • Stergios I. Roumeliotis
  • Daniel M. Helmick
  • Larry Matthies
چکیده

In this paper, an algorithm for autonomous stair climbing with a tracked vehicle is presented. The proposed method achieves robust performance under real-world conditions, without assuming prior knowledge of the stair geometry, the dynamics of the vehicle’s interaction with the stair surface, or lighting conditions. The approach relies on fast and accurate estimation of the robot’s heading and its position relative to the stair boundaries. An extended Kalman filter is used for quaternion-based attitude estimation, fusing rotational velocity measurements from a 3-axial gyroscope, and measurements of the stair edges acquired with an onboard camera. A two-tiered controller, comprised of a centeringand a heading-control module, utilizes the estimates to guide the robot rapidly, safely, and accurately upstairs. Both the theoretical analysis and implementation of the algorithm are presented in detail, and extensive experimental results demonstrating the algorithm’s performance are described. KEY WORDS—stair climbing, autonomous robots, inertial sensing, attitude estimation, computer vision.

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Dual Space Control of a Deployable Cable Driven Robot: Wave Based Approach

Known for their lower costs and numerous applications, cable robots are an attractive research field in robotic community. However, considering the fact that they require an accurate installation procedure and calibration routine, they have not yet found their true place in real-world applications. This paper aims to propose a new controller strategy that requires no meticulous calibration and ...

متن کامل

Neural Network Sensitivity to Inputs and Weights and its Application to Functional Identification of Robotics Manipulators

Neural networks are applied to the system identification problems using adaptive algorithms for either parameter or functional estimation of dynamic systems. In this paper the neural networks' sensitivity to input values and connections' weights, is studied. The Reduction-Sigmoid-Amplification (RSA) neurons are introduced and four different models of neural network architecture are proposed and...

متن کامل

Planar Molecular Dynamics Simulation of Au Clusters in Pushing Process

Based on the fact the manipulation of fine nanoclusters calls for more precise modeling, the aim of this paper is to conduct an atomistic investigation for interaction analysis of particle-substrate system for pushing and positioning purposes. In the present research, 2D molecular dynamics simulations have been used to investigate such behaviors. Performing the planar simulations can provide a ...

متن کامل

Robust image fusion using a statistical signal processing approach

Robust Mapping and Localization in Indoor Environments Using Sonar Data all 6 versions » JD Tardos, J Neira, PM Newman, JJ Leonard The International Journal of Robotics Research, 2002 ijr.sagepub.com The International Journal of Robotics Research Juan D Tardos, Jose Neira, Paul M Newman and John J Leonard Robust Mapping and Localization in Indoor Environments Using Sonar Data ... The Internatio...

متن کامل

Kinematic and Gait Analysis Implementation of an Experimental Radially Symmetric Six-Legged Walking Robot

As a robot could be stable statically standing on three or more legs, a six legged walking robot can be highly flexible in movements and perform different missions without dealing with serious kinematic and dynamic problems. An experimental six legged walking robot with 18 degrees of freedom is studied and built in this paper. The kinematic and gait analysis formulations are demonstrated by an e...

متن کامل

3D Scene and Object Classification Based on Information Complexity of Depth Data

In this paper the problem of 3D scene and object classification from depth data is addressed. In contrast to high-dimensional feature-based representation, the depth data is described in a low dimensional space. In order to remedy the curse of dimensionality problem, the depth data is described by a sparse model over a learned dictionary. Exploiting the algorithmic information theory, a new def...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

عنوان ژورنال:

دوره   شماره 

صفحات  -

تاریخ انتشار 2007