14,319 research outputs found
UcoSLAM: Simultaneous Localization and Mapping by Fusion of KeyPoints and Squared Planar Markers
This paper proposes a novel approach for Simultaneous Localization and
Mapping by fusing natural and artificial landmarks. Most of the SLAM approaches
use natural landmarks (such as keypoints). However, they are unstable over
time, repetitive in many cases or insufficient for a robust tracking (e.g. in
indoor buildings). On the other hand, other approaches have employed artificial
landmarks (such as squared fiducial markers) placed in the environment to help
tracking and relocalization. We propose a method that integrates both
approaches in order to achieve long-term robust tracking in many scenarios.
Our method has been compared to the start-of-the-art methods ORB-SLAM2 and
LDSO in the public dataset Kitti, Euroc-MAV, TUM and SPM, obtaining better
precision, robustness and speed. Our tests also show that the combination of
markers and keypoints achieves better accuracy than each one of them
independently.Comment: Paper submitted to Pattern Recognitio
Calibration and Sensitivity Analysis of a Stereo Vision-Based Driver Assistance System
Az http://intechweb.org/ alatti "Books" fĂĽl alatt kell rákeresni a "Stereo Vision" cĂmre Ă©s az 1. fejezetre
Realtime State Estimation with Tactile and Visual sensing. Application to Planar Manipulation
Accurate and robust object state estimation enables successful object
manipulation. Visual sensing is widely used to estimate object poses. However,
in a cluttered scene or in a tight workspace, the robot's end-effector often
occludes the object from the visual sensor. The robot then loses visual
feedback and must fall back on open-loop execution.
In this paper, we integrate both tactile and visual input using a framework
for solving the SLAM problem, incremental smoothing and mapping (iSAM), to
provide a fast and flexible solution. Visual sensing provides global pose
information but is noisy in general, whereas contact sensing is local, but its
measurements are more accurate relative to the end-effector. By combining them,
we aim to exploit their advantages and overcome their limitations. We explore
the technique in the context of a pusher-slider system. We adapt iSAM's
measurement cost and motion cost to the pushing scenario, and use an
instrumented setup to evaluate the estimation quality with different object
shapes, on different surface materials, and under different contact modes
A practical multirobot localization system
We present a fast and precise vision-based software intended for multiple robot localization. The core component of the software is a novel and efficient algorithm for black and white pattern detection. The method is robust to variable lighting conditions, achieves sub-pixel precision and its computational complexity is independent of the processed image size. With off-the-shelf computational equipment and low-cost cameras, the core algorithm is able to process hundreds of images per second while tracking hundreds of objects with a millimeter precision. In addition, we present the method's mathematical model, which allows to estimate the expected localization precision, area of coverage, and processing speed from the camera's intrinsic parameters and hardware's processing capacity. The correctness of the presented model and performance of the algorithm in real-world conditions is verified in several experiments. Apart from the method description, we also make its source code public at \emph{http://purl.org/robotics/whycon}; so, it can be used as an enabling technology for various mobile robotic problems
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