Sensor-based local homing using Omnidirectional Range and Intensity Sensing System for indoor mobile robot navigation

Bang, Seok Won; Yu, Wonpil; Chung, Myung Jin

doi:10.1109/iros.1995.526269

Cited by 5 publications

References 12 publications

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Mobile robot location identification system using reference interval-free continuous dynamic programming applied to time-varying images

Kojima¹,

Itoh²,

Oka³

1997

Syst. Comp. Jpn.

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In this paper, we propose a method which enables an autonomous mobile robot to identify its location without using markers. In this method, time‐varying images that the mobile robot acquires by walk‐through are used as a reference pattern, and when the robot walks along a path that it has previously passed, the location can be identified. In order to realize this capability, reference interval‐free continuous dynamic programming (RIFCDP) is applied. RIFCDP is an algorithm that detects an arbitrary section of the reference pattern which is similar to an arbitrary section of the input sequence, synchronized to each frame of the input sequence. Evaluation experiments have been performed in a real‐world environment with the input sequences acquired by moving along the same course of the reference patterns, on a shifted course, and at different speeds. The results show that location identification is possible in all cases without mistakenly recognizing an unknown place as a known place. © 1998 Scripta Technica, Syst Comp Jpn, 28(11): 1–10, 1997

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Mobile robot location identification system using reference interval-free continuous dynamic programming applied to time-varying images

Kojima¹,

Itoh²,

Oka³

1997

Syst. Comp. Jpn.

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Cataglyphis: An autonomous sample return rover

Ohi

Lassak

et al. 2017

Journal of Field Robotics

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This paper presents the design of Cataglyphis, a research rover that won the NASA Sample Return Robot Centennial Challenge in 2015. During the challenge, Cataglyphis was the only robot that was able to autonomously find, retrieve, and return multiple types of samples in a large natural environment without using Earth‐specific sensors such as GPS and magnetic compasses. It navigates through a fusion of measurements collected from inertial sensors, wheel encoders, a nodding Lidar, a set of ranging radios, a camera on a panning platform, and a sun sensor. In addition to visual detection of a homing beacon, computer vision algorithms provide the sample detection, identification, and localization capabilities, with low false positive and false negative rates demonstrated during the competition. The mission planning and control software enables robot behaviors, determines sequences of actions, and helps the robot to recover from various failure conditions. A compliant, under‐actuated manipulator conforms to the natural terrain before picking up samples of various size, weight, and shape.

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Real-Time Omnidirectional Image Sensors

Yagi

Yachida

2004

International Journal of Computer Vision

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Sensor-based local homing using Omnidirectional Range and Intensity Sensing System for indoor mobile robot navigation

Cited by 5 publications

References 12 publications

Mobile robot location identification system using reference interval-free continuous dynamic programming applied to time-varying images

Mobile robot location identification system using reference interval-free continuous dynamic programming applied to time-varying images

Cataglyphis: An autonomous sample return rover

Real-Time Omnidirectional Image Sensors

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