A Review: Simultaneous Localization and Mapping in Application to Autonomous Robot

Research Direction ◽

Autonomous Robot ◽

Unknown Environment ◽

Computational Problem ◽

Open Issues

The important characteristic that could assist in autonomous navigation is the ability of a mobile robot to concurrently construct a map for an unknown environment and localize itself within the same environment. This computational problem is known as Simultaneous Localization and Mapping (SLAM). In literature, researchers have studied this approach extensively and have proposed a lot of improvement towards it. More so, we are experiencing a steady transition of this technology to industries. However, there are still setbacks limiting the full acceptance of this technology even though the research had been conducted over the last 30 years. Thus, to determine the problems facing SLAM, this paper conducted a review on various foundation and recent SLAM algorithms. Challenges and open issues alongside the research direction for this area were discussed. However, towards addressing the problem discussed, a novel SLAM technique will be proposed.

Autonomous navigation in unknown environment using sliding mode SLAM and genetic algorithm

Intelligence & Robotics ◽

10.20517/ir.2021.09 ◽

2021 ◽

Author(s):

Salvador Ortiz ◽

Wen Yu

Keyword(s):

Genetic Algorithm ◽

Path Planning ◽

Sliding Mode Control ◽

Autonomous Navigation ◽

Sliding Mode ◽

Planning Method ◽

Unknown Environment ◽

Bounded Uncertainties

In this paper, sliding mode control is combined with the classical simultaneous localization and mapping (SLAM) method. This combination can overcome the problem of bounded uncertainties in SLAM. With the help of genetic algorithm, our novel path planning method shows many advantages compared with other popular methods.

Advanced Methodologies and Technologies in Artificial Intelligence, Computer Simulation, and Human-Computer Interaction - Advances in Computer and Electrical Engineering ◽

Using Global Appearance Descriptors to Solve Topological Visual SLAM

10.4018/978-1-5225-7368-5.ch082 ◽

2019 ◽

pp. 1127-1140

Author(s):

Lorenzo Fernández Rojo ◽

Luis Paya ◽

Francisco Amoros ◽

Oscar Reinoso

Keyword(s):

Computer Vision ◽

Mobile Robot ◽

Mobile Robots ◽

Visual Slam ◽

Sources Of Information ◽

Topological Approach ◽

Unknown Environment ◽

Omnidirectional Images

Mobile robots have extended to many different environments, where they have to move autonomously to fulfill an assigned task. With this aim, it is necessary that the robot builds a model of the environment and estimates its position using this model. These two problems are often faced simultaneously. This process is known as SLAM (simultaneous localization and mapping) and is very common since when a robot begins moving in a previously unknown environment it must start generating a model from the scratch while it estimates its position simultaneously. This chapter is focused on the use of computer vision to solve this problem. The main objective is to develop and test an algorithm to solve the SLAM problem using two sources of information: (1) the global appearance of omnidirectional images captured by a camera mounted on the mobile robot and (2) the robot internal odometry. A hybrid metric-topological approach is proposed to solve the SLAM problem.

2018 International Conference on Computational Approach in Smart Systems Design and Applications (ICASSDA) ◽

Mobile Robot Based Simultaneous Localization and Mapping in UniMAP's Unknown Environment

10.1109/icassda.2018.8477629 ◽

2018 ◽

Cited By ~ 1

Author(s):

Wan Abdul Syaqur ◽

Ahmad Shakaff Ali Yeon ◽

Abu Hassan Abdullah ◽

Kamarulzaman Kamarudin ◽

Retnam Visvanathan ◽

...

Keyword(s):

Mobile Robot ◽

Unknown Environment ◽

Localization And Mapping

Using Global Appearance Descriptors to Solve Topological Visual SLAM

Encyclopedia of Information Science and Technology, Fourth Edition ◽

10.4018/978-1-5225-2255-3.ch597 ◽

2018 ◽

pp. 6894-6905

Author(s):

Lorenzo Fernández Rojo ◽

Luis Paya ◽

Francisco Amoros ◽

Oscar Reinoso

Keyword(s):

Computer Vision ◽

Mobile Robot ◽

Mobile Robots ◽

Visual Slam ◽

Sources Of Information ◽

Topological Approach ◽

Unknown Environment ◽

Omnidirectional Images

Nowadays, mobile robots have extended to many different environments, where they have to move autonomously to fulfill an assigned task. With this aim, it is necessary that the robot builds a model of the environment and estimates its position using this model. These two problems are often faced simultaneously. This process is known as SLAM (Simultaneous Localization and Mapping) and is very common since when a robot begins moving in a previously unknown environment it must start generating a model from the scratch while it estimates its position simultaneously. This work is focused on the use of computer vision to solve this problem. The main objective is to develop and test an algorithm to solve the SLAM problem using two sources of information: (a) the global appearance of omnidirectional images captured by a camera mounted on the mobile robot and (b) the robot internal odometry. A hybrid metric-topological approach is proposed to solve the SLAM problem.

Indoor Autonomous Navigation Technology Research Based on Lidar for Quad-Copter Aerial Robot

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.538.371 ◽

2014 ◽

Vol 538 ◽

pp. 371-374

Author(s):

Zhi Jun Bai ◽

Yang Feng Ji ◽

Liao Ni Wu ◽

Qi Lin

Keyword(s):

Navigation System ◽

Autonomous Navigation ◽

Technology Research ◽

Unknown Environment ◽

Monocular Camera ◽

Aerial Robot ◽

Test Result ◽

Autonomous Navigation System

An indoor autonomous navigation system without GPS has been developed, based on the platform of quad-copter, which may fulfill the task of searching, identifying and entering the target room in a building with multi-rooms corridor. A pose sensor was utilized to stabilize the aircraft. The SLAM (Simultaneous Localization and Mapping) and plan route in unknown environment have been created by a 2D lidar. A calibrated monocular camera has been used to recognize different marks to make sure the vehicle to enter the target room. The test result showed that the indoor autonomous navigation technology based on lidar for quad-copter aerial robot is feasible and successful.

Simulation and Experimental Evaluation of the EKF Simultaneous Localization and Mapping Algorithm on the Wifibot Mobile Robot

Journal of Artificial Intelligence and Soft Computing Research ◽

10.1515/jaiscr-2018-0006 ◽

2018 ◽

Vol 8 (2) ◽

pp. 91-101 ◽

Cited By ~ 3

Author(s):

Noura Ayadi ◽

Nabil Derbel ◽

Nicolas Morette ◽

Cyril Novales ◽

Gérard Poisson

Keyword(s):

Mobile Robot ◽

Autonomous Navigation ◽

Large Scale ◽

Research Field ◽

Small Scale ◽

Mapping Algorithm ◽

Highly Active ◽

Active Research

Abstract In recent years, autonomous navigation for mobile robots has been considered a highly active research field. Within this context, we are interested to apply the Simultaneous Localization And Mapping (SLAM) approach for a wheeled mobile robot. The Extended Kalman Filter has been chosen to perform the SLAM algorithm. In this work, we explicit all steps of the approach. Performances of the developed algorithm have been assessed through simulation in the case of a small scale map. Then, we present several experiments on a real robot that are proceeded in order to exploit a programmed SLAM unit and to generate the navigation map. Based on experimental results, simulation of the SLAM method in the case of a large scale map is then realized. Obtained results are exploited in order to evaluate and compare the algorithm’s consistency and robustness for both cases.

A Study of Autonomous Navigation of a Robot Model based on SLAM, ROS, and Kinect

International Journal of Engineering & Technology ◽

10.14419/ijet.v7i3.33.18517 ◽

2018 ◽

Vol 7 (3.33) ◽

pp. 28

Author(s):

Asilbek Ganiev ◽

Kang Hee Lee

Keyword(s):

Operating System ◽

Mobile Robot ◽

Mobile Robots ◽

Autonomous Navigation ◽

Target Point ◽

Robot Operating System ◽

Model Based ◽

Starting Point

In this paper, we used a robot operating system (ROS) that is designed to work with mobile robots. ROS provides us with simultaneous localization and mapping of the environment, and here it is used to autonomously navigate a mobile robot simulator between specified points. Also, when the mobile robot automatically navigates between the starting point and the target point, it bypasses obstacles; and if necessary, sets a new path of the route to reach the goal point.

Autonomous Navigation and Mapping for Mobile Robot in Unknown Environment Using Line Segments

ASME 2016 Conference on Information Storage and Processing Systems ◽

10.1115/isps2016-9560 ◽

2016 ◽

Author(s):

Chunlin Song ◽

Cheng Chen ◽

Naigang Cui

Keyword(s):

Mobile Robot ◽

Autonomous Navigation ◽

Autonomous Robots ◽

Line Segments ◽

Unknown Environment ◽

Coupled Problem ◽

Environment Exploration ◽

Planet Exploration ◽

Robotic Research

Used widely in military and civil applications, autonomous robots have shown promising in planet exploration, seabed survey, and disaster rescue. A lot of robotic research concentrates on localization and mapping dealing with the basic problems in robotic research: “Where I am?” and “How is the environment like?”. The two problems consist a coupled problem named Simultaneous Localization and Mapping (SLAM) in unknown environment exploration. This problem is summarized by Hugh D. Whyte in his paper published in 1991 [1]. Forced by requirement of motion in unknown environment, many researchers in robotics make efforts to solve SLAM problem in recent decades.