Path tracking by a mobile robot equipped with only a downward facing camera

Nagai, Isaku; Watanabe, Keigo

doi:10.1109/iros.2015.7354239

Cited by 9 publications

(9 citation statements)

References 18 publications

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“…x and v (f ) y respectively, and when the angle of rotation during the rotary motion is defined as θ (f ) , the keypoint's movement position of X-axis and Y-axis, x (f +1) and y (f +1) can be calculated from equation (2).…”

Section: B Akaze Feature Matching With Estimation Methodsmentioning

confidence: 99%

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AKAZE-Based Visual Odometry From Floor Images Supported by Acceleration Models

Nakashima

Morio

2019

IEEE Access

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To realize the self-localization of autonomous robots, methods for the 2D motion measurement of robots are required. In this research, a self-localization system using a CCD camera is proposed. In the proposed system, the self-localization is estimated by movement tracking using some keypoints detected from the floor images captured by the CCD camera. For the illumination of floor image, two LED illuminate are used. These lighting systems are installed in such a way that lit from both sides of the floor and parallel to the floor so that some minimal bumps or original veins are captured from the floor. An accelerated KAZE feature is applied in the proposed system for keypoint detection and for computing resulting in the generation of the descriptor. In the estimation, the location information from the previous step and the estimated position one frame ahead are used. Using the estimated result and computed descriptor, the proposed system matches the nearest keypoint between the estimated keypoint detected from the previous floor image and the keypoint detected from the next floor image at the beginning. The Hamming distance is employed in the proposed system to evaluate the matching. If the Hamming distance is longer than a threshold, the proposed system tries to match from the 2nd nearest keypoint. Based on an experiment in which the measurement distance and computation time are investigated, the effectiveness of the proposed method is confirmed. INDEX TERMS Visual odometry, vision measurement, image motion analysis, odometry measurement, AKAZE features, image matching.

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Section: B Akaze Feature Matching With Estimation Methodsmentioning

confidence: 99%

“…of template matching methods applied in self-localization are Nagai's downward facing camera method [2], Savan's ground vehicle method [3] and Andrew's real-time stereo visual odometry method [4]. However, the method using template matching needs to control the illumination of light.…”

Section: Introductionmentioning

confidence: 99%

AKAZE-Based Visual Odometry From Floor Images Supported by Acceleration Models

Nakashima

Morio

2019

IEEE Access

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“…This approach has some advantages over approaches using forward-facing cameras: it does not have any issues with occlusions of the surrounding, it works in environments without static landmarks, and it can be made independent of the surrounding lighting. Previous work has shown that reliable high-accuracy pose estimates can be achieved with ground texture based localization on typical ground texture types, such as asphalt and concrete [3], [4], [5], [6], [11], [13], [16].…”

Section: Introductionmentioning

confidence: 99%

Model-Based Parameter Optimization for Ground Texture Based Localization Methods

Schmid,

Simon,

Mester

2021

Preprint

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A promising approach to accurate positioning of robots is ground texture based localization. It is based on the observation that visual features of ground images enable fingerprint-like place recognition. We tackle the issue of efficient parametrization of such methods, deriving a prediction model for localization performance, which requires only a small collection of sample images of an application area. In a first step, we examine whether the model can predict the effects of changing one of the most important parameters of feature-based localization methods: the number of extracted features. We examine two localization methods, and in both cases our evaluation shows that the predictions are sufficiently accurate. Since this model can be used to find suitable values for any parameter, we then present a holistic parameter optimization framework, which finds suitable texture-specific parameter configurations, using only the model to evaluate the considered parameter configurations.

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“…Visual odometry for mobile robots and automobiles has been recently developed using downwardfacing standard cameras [32][33][34][35][36] and optical mice [37][38][39], as well as custom-made OF sensors [40,41], since the visual patterns and light conditions encountered in this way are relatively uniform, and the distance between the sensors and the ground usually changes slightly. In most cases, the authors used the car-like non-holonomic constraint to estimate the vehicle's position and orientation using simple methods involving low computational costs.…”

Section: Introductionmentioning

confidence: 99%

“…However, solutions based on standard cameras [33,36] still fail to cope with high-dynamic-range lighting conditions, as well as being impeded by the low frame rate and the high computational cost of the image processing: only a narrow range of low velocity measurements can often be obtained using this approach.…”

Section: Introductionmentioning

confidence: 99%

Minimalistic optic flow sensors applied to indoor and outdoor visual guidance and odometry on a car-like robot

2016

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Here we present a novel bio-inspired optic flow (OF) sensor and its application to visual guidance and odometry on a low-cost car-like robot called BioCarBot. The minimalistic OF sensor was robust to high-dynamic-range lighting conditions and to various visual patterns encountered thanks to its MAPIX auto-adaptive pixels and the new cross-correlation OF algorithm implemented. The low-cost car-like robot estimated its velocity and steering angle, and therefore its position and orientation, via an extended Kalman filter (EKF) using only two downward-facing OF sensors and the Ackerman steering model. Indoor and outdoor experiments were carried out in which the robot was driven in the closed-loop mode based on the velocity and steering angle estimates. The experimental results obtained show that our novel OF sensor can deliver high-frequency measurements ([Formula: see text]) in a wide OF range (1.5-[Formula: see text]) and in a 7-decade high-dynamic light level range. The OF resolution was constant and could be adjusted as required (up to [Formula: see text]), and the OF precision obtained was relatively high (standard deviation of [Formula: see text] with an average OF of [Formula: see text], under the most demanding lighting conditions). An EKF-based algorithm gave the robot's position and orientation with a relatively high accuracy (maximum errors outdoors at a very low light level: [Formula: see text] and [Formula: see text] over about [Formula: see text] and [Formula: see text]) despite the low-resolution control systems of the steering servo and the DC motor, as well as a simplified model identification and calibration. Finally, the minimalistic OF-based odometry results were compared to those obtained using measurements based on an inertial measurement unit (IMU) and a motor's speed sensor.

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Path tracking by a mobile robot equipped with only a downward facing camera

Cited by 9 publications

References 18 publications

AKAZE-Based Visual Odometry From Floor Images Supported by Acceleration Models

AKAZE-Based Visual Odometry From Floor Images Supported by Acceleration Models

Model-Based Parameter Optimization for Ground Texture Based Localization Methods

Minimalistic optic flow sensors applied to indoor and outdoor visual guidance and odometry on a car-like robot

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