scholarly journals Cooperative Exploration by Multi-Robots without Global Localization

10.5772/5682 ◽  
2007 ◽  
Vol 4 (3) ◽  
pp. 36 ◽  
Author(s):  
Shi Chao-xia ◽  
Hong Bing-rong ◽  
Wang Yan-qing
Keyword(s):  
Reference Frame ◽  
Mobile Robotics ◽  
Fundamental Problem ◽  
Global Localization ◽  
Scale Invariant ◽  
Topological Map ◽  
Invariant Features ◽  
Unknown Environments ◽  
Efficient Exploration ◽  
Cooperative Exploration

Efficient exploration of unknown environments is a fundamental problem in mobile robotics. We propose a novel topological map whose nodes are represented with the range finder's free beams together with the visual scale-invariant features. The topological map enables teams of robots to efficiently explore environments from different, unknown locations without knowing their initial poses, relative poses and global poses in a certain world reference frame. The experiments of map merging and coordinated exploration demonstrate the proposed map is not only easy for merging, but also convenient for robust and efficient explorations in unknown environments.

scholarly journals Spectrum of power laws for curved hand movements

2015 ◽  
Vol 112 (29) ◽  
pp. E3950-E3958 ◽  
Author(s):  
Dongsung Huh ◽  
Terrence J. Sejnowski
Keyword(s):  
Optimal Control ◽  
Motor Planning ◽  
Power Laws ◽  
Angular Frequency ◽  
Control Model ◽  
Hand Movements ◽  
Local Curvature ◽  
Scale Invariant ◽  
The Past ◽  
Invariant Features

In a planar free-hand drawing of an ellipse, the speed of movement is proportional to the −1/3 power of the local curvature, which is widely thought to hold for general curved shapes. We investigated this phenomenon for general curved hand movements by analyzing an optimal control model that maximizes a smoothness cost and exhibits the −1/3 power for ellipses. For the analysis, we introduced a new representation for curved movements based on a moving reference frame and a dimensionless angle coordinate that revealed scale-invariant features of curved movements. The analysis confirmed the power law for drawing ellipses but also predicted a spectrum of power laws with exponents ranging between 0 and −2/3 for simple movements that can be characterized by a single angular frequency. Moreover, it predicted mixtures of power laws for more complex, multifrequency movements that were confirmed with human drawing experiments. The speed profiles of arbitrary doodling movements that exhibit broadband curvature profiles were accurately predicted as well. These findings have implications for motor planning and predict that movements only depend on one radian of angle coordinate in the past and only need to be planned one radian ahead.

scholarly journals Topological Frontier-Based Exploration and Map-Building Using Semantic Information

Sensors ◽  
2019 ◽  
Vol 19 (20) ◽  
pp. 4595 ◽  
Author(s):  
Clara Gomez ◽  
Alejandra C. Hernandez ◽  
Ramon Barber
Keyword(s):  
Open Space ◽  
Semantic Information ◽  
State Of The Art ◽  
Fundamental Problem ◽  
Cost Utility ◽  
Indoor Environments ◽  
Map Building ◽  
Topological Map ◽  
Unknown Area ◽  
Closure Algorithm

Exploration of unknown environments is a fundamental problem in autonomous robotics that deals with the complexity of autonomously traversing an unknown area while acquiring the most important information of the environment. In this work, a mobile robot exploration algorithm for indoor environments is proposed. It combines frontier-based concepts with behavior-based strategies in order to build a topological representation of the environment. Frontier-based approaches assume that, to gain the most information of an environment, the robot has to move to the regions on the boundary between open space and unexplored space. The novelty of this work is in the semantic frontier classification and frontier selection according to a cost–utility function. In addition, a probabilistic loop closure algorithm is proposed to solve cyclic situations. The system outputs a topological map of the free areas of the environment for further navigation. Finally, simulated and real-world experiments have been carried out, their results and the comparison to other state-of-the-art algorithms show the feasibility of the exploration algorithm proposed and the improvement that it offers with regards to execution time and travelled distance.

scholarly journals Image Detection System Using Image Processing

2021 ◽  
Vol 9 (VI) ◽  
pp. 5356-5362
Author(s):  
Mohini Gawande
Keyword(s):  
Image Processing ◽  
Computer Vision ◽  
Detection System ◽  
Estimation Method ◽  
Scale Invariant ◽  
Matrix Estimation ◽  
Speeded Up Robust Features ◽  
Invariant Features ◽  
Marketing Analysis ◽  
New Strategies

The increasing popularity of Social Networks makes change the way people interact. These interactions produce a huge amount of data and it opens the door to new strategies and marketing analysis. According to Instagram and Tumblr, an average of 80 and 59 million photos respectively are published every day, and those pictures contain several implicit or explicit brand logos. Image recognition is one of the most important fields of image processing and computer vision. The CNNs are a very effective class of neural networks that is highly effective at the task of image classifying, object detection and other computer vision problems.in recent years, several scale- invariant features have been proposed in literature, this paper analyzes the usage of Speeded Up Robust Features (SURF) as local descriptors, and as we will see, they are not only scale-invariant features, but they also offer the advantage of being computed very efficiently. Furthermore, a fundamental matrix estimation method based on the RANSAC is applied.

Detection of Relative Motion

Perception ◽  
1996 ◽  
Vol 25 (1_suppl) ◽  
pp. 71-71
Author(s):  
M A Hogervorst ◽  
A M L Kappers ◽  
J J Koenderink ◽  
J Bongaerts
Keyword(s):  
Reference Frame ◽  
Relative Motion ◽  
Detection System ◽  
Temporal Frequency ◽  
Critical Time ◽  
Critical Distance ◽  
Viewing Distance ◽  
Scale Invariant ◽  
Motion Direction ◽  
Threshold Amplitude

We measured human sensitivity to the relative motion of blobs moving in the peripheral visual field. The stimuli consisted of one or two blobs (Gaussian luminance profiles) oscillating relative to an (invisible) reference frame which rotated with constant angular velocity about a fixation point. We determined thresholds for detecting the oscillation of different configurations of one or two blobs as a function of velocity, eccentricity (viewing distance), and temporal frequency. By determining thresholds as a function of frequency the temporal characteristics of the detection system could be revealed. Thresholds are higher for oscillations in the motion direction of the reference frame than perpendicular to it. No influence has been found of the position of the blobs in the frame of reference. The thresholds are scale-invariant. For low frequencies (<2 Hz) the threshold amplitude of the velocity modulation is constant whereas for high frequencies (>2 Hz) the threshold amplitude of the position modulation is constant. This behaviour can be well described by a model which detects the oscillations whenever, within a critical time (of about 200 ms for two blobs), the relative displacement is larger than a critical distance. The critical distance shows the same dependence on velocity as the span in the bilocal detector model of Koenderink et al (1985 Journal of the Optical Society of America A2 252 – 259).

Sign in / Sign up

Export Citation Format

Share Document