scholarly journals Optimal Frontier-Based Autonomous Exploration in Unconstructed Environment Using RGB-D Sensor

Sensors ◽  
2020 ◽  
Vol 20 (22) ◽  
pp. 6507 ◽  
Author(s):  
Liang Lu ◽  
Carlos Redondo ◽  
Pascual Campoy
Keyword(s):  
Clustering Algorithm ◽  
Information Gain ◽  
State Of The Art ◽  
Search And Rescue ◽  
Autonomous Exploration ◽  
Aerial Robots ◽  
Exploration Time ◽  
Feasible Path ◽  
Path Planner ◽  
To Receive

Aerial robots are widely used in search and rescue applications because of their small size and high maneuvering. However, designing an autonomous exploration algorithm is still a challenging and open task, because of the limited payload and computing resources on board UAVs. This paper presents an autonomous exploration algorithm for the aerial robots that shows several improvements for being used in the search and rescue tasks. First of all, an RGB-D sensor is used to receive information from the environment and the OctoMap divides the environment into obstacles, free and unknown spaces. Then, a clustering algorithm is used to filter the frontiers extracted from the OctoMap, and an information gain based cost function is applied to choose the optimal frontier. At last, the feasible path is given by A* path planner and a safe corridor generation algorithm. The proposed algorithm has been tested and compared with baseline algorithms in three different environments with the map resolutions of 0.2 m, and 0.3 m. The experimental results show that the proposed algorithm has a shorter exploration path and can save more exploration time when compared with the state of the art. The algorithm has also been validated in the real flight experiments.

scholarly journals From ERL to MBZIRC: Development of An Aerial-Ground Robotic Team for Search and Rescue

2021 ◽  
Author(s):  
Barbara Arbanas ◽  
Frano Petric ◽  
Ana Batinović ◽  
Marsela Polić ◽  
Ivo Vatavuk ◽  
...  
Keyword(s):  
State Of The Art ◽  
The State ◽  
Search And Rescue ◽  
System Specification ◽  
Autonomous Exploration ◽  
Unstructured Environments ◽  
Software Modules ◽  
Detection Of Objects ◽  
Additional Improvement ◽  
Robotic Teams

This chapter describes the efforts of the LARICS team in the 2019 European Robotics League (ERL) Emergency Robots and the 2020 Mohamed Bin Zayed International Robotics Challenge (MBZIRC) robotics competitions. We focus on the implementation of hardware and software modules that enable the deployment of aerial-ground robotic teams in unstructured environments for joint missions. In addition to the overall system specification, we outline the main algorithms for operation in such conditions: autonomous exploration of unknown environments and detection of objects of interest. Analysis of the results shows the success of the developed system in the competition arena of two of the largest outdoor robotics challenges. Throughout the chapter, we highlight the evolution of the robotic system based on the experience gained in the ERL competition. We conclude the chapter with key findings and additional improvement ideas to advance the state of the art in search and rescue applications of heterogeneous robotic teams.

Segmentation of SAR Image using Fuzzy C-Means and Filters

2020 ◽  
Vol 8 (1) ◽  
pp. 84-90
Author(s):  
R. Lalchhanhima ◽  
◽  
Debdatta Kandar ◽  
R. Chawngsangpuii ◽  
Vanlalmuansangi Khenglawt ◽  
...  
Keyword(s):  
Clustering Algorithm ◽  
State Of The Art ◽  
Speckle Noise ◽  
Synthetic Aperture Radar Image ◽  
Synthetic Aperture ◽  
Sar Image ◽  
Spatial Filters ◽  
Fuzzy C Means ◽  
Automatic Clustering ◽  
Intensity Information

Fuzzy C-Means is an unsupervised clustering algorithm for the automatic clustering of data. Synthetic Aperture Radar Image Segmentation has been a challenging task because of the presence of speckle noise. Therefore the segmentation process can not directly rely on the intensity information alone but must consider several derived features in order to get satisfactory segmentation results. In this paper, it is attempted to use the fuzzy nature of classification for the purpose of unsupervised region segmentation in which FCM is employed. Different features are obtained by filtering of the image by using different spatial filters and are selected for segmentation criteria. The segmentation performance is determined by the accuracy compared with a different state of the art techniques proposed recently.

scholarly journals Malaria parasite detection in thick blood smear microscopic images using modified YOLOV3 and YOLOV4 models

2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Fetulhak Abdurahman ◽  
Kinde Anlay Fante ◽  
Mohammed Aliy
Keyword(s):  
Object Detection ◽  
Malaria Parasite ◽  
Blood Smear ◽  
Clustering Algorithm ◽  
State Of The Art ◽  
Detection Accuracy ◽  
Small Object ◽  
Thick Blood Smear ◽  
Malaria Parasites ◽  
Microscopic Images

Abstract Background Manual microscopic examination of Leishman/Giemsa stained thin and thick blood smear is still the “gold standard” for malaria diagnosis. One of the drawbacks of this method is that its accuracy, consistency, and diagnosis speed depend on microscopists’ diagnostic and technical skills. It is difficult to get highly skilled microscopists in remote areas of developing countries. To alleviate this problem, in this paper, we propose to investigate state-of-the-art one-stage and two-stage object detection algorithms for automated malaria parasite screening from microscopic image of thick blood slides. Results YOLOV3 and YOLOV4 models, which are state-of-the-art object detectors in accuracy and speed, are not optimized for detecting small objects such as malaria parasites in microscopic images. We modify these models by increasing feature scale and adding more detection layers to enhance their capability of detecting small objects without notably decreasing detection speed. We propose one modified YOLOV4 model, called YOLOV4-MOD and two modified models of YOLOV3, which are called YOLOV3-MOD1 and YOLOV3-MOD2. Besides, new anchor box sizes are generated using K-means clustering algorithm to exploit the potential of these models in small object detection. The performance of the modified YOLOV3 and YOLOV4 models were evaluated on a publicly available malaria dataset. These models have achieved state-of-the-art accuracy by exceeding performance of their original versions, Faster R-CNN, and SSD in terms of mean average precision (mAP), recall, precision, F1 score, and average IOU. YOLOV4-MOD has achieved the best detection accuracy among all the other models with a mAP of 96.32%. YOLOV3-MOD2 and YOLOV3-MOD1 have achieved mAP of 96.14% and 95.46%, respectively. Conclusions The experimental results of this study demonstrate that performance of modified YOLOV3 and YOLOV4 models are highly promising for detecting malaria parasites from images captured by a smartphone camera over the microscope eyepiece. The proposed system is suitable for deployment in low-resource setting areas.

Information-driven Fast Marching Autonomous Exploration with Aerial Robots

2021 ◽  
pp. 1-1
Author(s):  
Ping Zhong ◽  
Bolei Chen ◽  
Siyi Lu ◽  
Xiaoxi Meng ◽  
Yixiong Liang
Keyword(s):  
Fast Marching ◽  
Autonomous Exploration ◽  
Aerial Robots

Estimated path information gain-based robot exploration under perceptual uncertainty

Robotica ◽  
2022 ◽  
pp. 1-17
Author(s):  
Jie Liu ◽  
Chaoqun Wang ◽  
Wenzheng Chi ◽  
Guodong Chen ◽  
Lining Sun
Keyword(s):  
Decision Making ◽  
Topological Structure ◽  
Information Gain ◽  
State Of The Art ◽  
Selection Process ◽  
Random Trees ◽  
Experimental Results ◽  
Restricted Area ◽  
Structure Information ◽  
Path Information

Abstract At present, the frontier-based exploration has been one of the mainstream methods in autonomous robot exploration. Among the frontier-based algorithms, the method of searching frontiers based on rapidly exploring random trees consumes less computing resources with higher efficiency and performs well in full-perceptual scenarios. However, in the partially perceptual cases, namely when the environmental structure is beyond the perception range of robot sensors, the robot often lingers in a restricted area, and the exploration efficiency is reduced. In this article, we propose a decision-making method for robot exploration by integrating the estimated path information gain and the frontier information. The proposed method includes the topological structure information of the environment on the path to the candidate frontier in the frontier selection process, guiding the robot to select a frontier with rich environmental information to reduce perceptual uncertainty. Experiments are carried out in different environments with the state-of-the-art RRT-exploration method as a reference. Experimental results show that with the proposed strategy, the efficiency of robot exploration has been improved obviously.

FAST RRT* 3D-Sliced Planner for Autonomous Exploration Using MAVs

2021 ◽  
pp. 1-12
Author(s):  
Á. Martínez Novo ◽  
Liang Lu ◽  
Pascual Campoy
Keyword(s):  
State Of The Art ◽  
Micro Aerial Vehicles ◽  
Autonomous Exploration ◽  
Signed Distance ◽  
Aerial Vehicles ◽  
3D Environment ◽  
Frontier Points ◽  
Computational Resources ◽  
Next Best View ◽  
Signed Distance Field

This paper addresses the challenge to build an autonomous exploration system using Micro-Aerial Vehicles (MAVs). MAVs are capable of flying autonomously, generating collision-free paths to navigate in unknown areas and also reconstructing the environment at which they are deployed. One of the contributions of our system is the “3D-Sliced Planner” for exploration. The main innovation is the low computational resources needed. This is because Optimal-Frontier-Points (OFP) to explore are computed in 2D slices of the 3D environment using a global Rapidly-exploring Random Tree (RRT) frontier detector. Then, the MAV can plan path routes to these points to explore the surroundings with our new proposed local “FAST RRT* Planner” that uses a tree reconnection algorithm based on cost, and a collision checking algorithm based on Signed Distance Field (SDF). The results show the proposed explorer takes 43.95% less time to compute exploration points and paths when compared with the State-of-the-Art represented by the Receding Horizon Next Best View Planner (RH-NBVP) in Gazebo simulations.

Field experiments and public policy: festina lente

2020 ◽  
Vol 5 (1) ◽  
pp. 117-124 ◽  
Author(s):  
GLENN W. HARRISON
Keyword(s):  
Public Policy ◽  
Field Experiments ◽  
State Of The Art ◽  
Welfare Effects ◽  
Current State ◽  
To Receive

AbstractThe current state of the art in field experiments does not give me any confidence that we should be assuming that we have anything worth scaling, assuming we really care about the expected welfare of those about to receive the instant intervention. At the very least, we should be honest and explicit about the need for strong priors about the welfare effects of changes in averages of observables to warrant scaling. What we need is a healthy dose of theory and the implied econometrics.

scholarly journals Industrial marketing research: Theory and practice

1982 ◽  
Vol 13 (2) ◽  
pp. 70-75
Author(s):  
Russell Abratt
Keyword(s):  
South Africa ◽  
State Of The Art ◽  
Marketing Research ◽  
Theory And Practice ◽  
Consumer Market ◽  
Simple Method ◽  
Industrial Marketing ◽  
Industrial Companies ◽  
Marketing Planning ◽  
To Receive

Industrial marketing research is generally speaking a low priority item for industrial companies in South Africa. However, marketing research should form the basis of most marketing planning. Marketing research budgets in industrial companies are usually small because management feels that most projects are either too expensive or too time consuming. The objective of this article is to show that industrial marketing research need not be expensive or time consuming. Industrial marketing research has failed to receive much attention in standard marketing books and journals, in spite of the fact that the size of the industrial market is larger than the consumer market in South Africa. The author discusses a simple method which can be followed by people in industrial companies with little or no marketing background. The scope of industrial marketing research and the planning of an industrial research project are discussed; besides a report on a field study undertaken among 20 industrial plastics manufacturers on the Witwatersrand to establish the 'state of the art' as far as their marketing research was concerned.

scholarly journals Automatic spike sorting for high-density microelectrode arrays

2018 ◽  
Vol 120 (6) ◽  
pp. 3155-3171 ◽  
Author(s):  
Roland Diggelmann ◽  
Michele Fiscella ◽  
Andreas Hierlemann ◽  
Felix Franke
Keyword(s):  
Principal Component Analysis ◽  
Clustering Algorithm ◽  
State Of The Art ◽  
Microelectrode Arrays ◽  
Principal Component ◽  
Component Analysis ◽  
High Density ◽  
Sorting Algorithm ◽  
Spike Sorting ◽  
Recording Electrodes

High-density microelectrode arrays can be used to record extracellular action potentials from hundreds to thousands of neurons simultaneously. Efficient spike sorters must be developed to cope with such large data volumes. Most existing spike sorting methods for single electrodes or small multielectrodes, however, suffer from the “curse of dimensionality” and cannot be directly applied to recordings with hundreds of electrodes. This holds particularly true for the standard reference spike sorting algorithm, principal component analysis-based feature extraction, followed by k-means or expectation maximization clustering, against which most spike sorters are evaluated. We present a spike sorting algorithm that circumvents the dimensionality problem by sorting local groups of electrodes independently with classical spike sorting approaches. It is scalable to any number of recording electrodes and well suited for parallel computing. The combination of data prewhitening before the principal component analysis-based extraction and a parameter-free clustering algorithm obviated the need for parameter adjustments. We evaluated its performance using surrogate data in which we systematically varied spike amplitudes and spike rates and that were generated by inserting template spikes into the voltage traces of real recordings. In a direct comparison, our algorithm could compete with existing state-of-the-art spike sorters in terms of sensitivity and precision, while parameter adjustment or manual cluster curation was not required. NEW & NOTEWORTHY We present an automatic spike sorting algorithm that combines three strategies to scale classical spike sorting techniques for high-density microelectrode arrays: 1) splitting the recording electrodes into small groups and sorting them independently; 2) clustering a subset of spikes and classifying the rest to limit computation time; and 3) prewhitening the spike waveforms to enable the use of parameter-free clustering. Finally, we combined these strategies into an automatic spike sorter that is competitive with state-of-the-art spike sorters.

Sign in / Sign up

Export Citation Format

Share Document