scholarly journals Multirobot FastSLAM Algorithm Based on Landmark Consistency Correction

2014 ◽  
Vol 2014 ◽  
pp. 1-7
Author(s):  
Shi-Ming Chen ◽  
Jun-Feng Yuan ◽  
Fang Zhang ◽  
Hua-Jing Fang
Keyword(s):  
Multiple Robots ◽  
Localization And Mapping ◽  
Resampling Procedure ◽  
Consensus Filter ◽  
Simulation Results

Considering the influence of uncertain map information on multirobot SLAM problem, a multirobot FastSLAM algorithm based on landmark consistency correction is proposed. Firstly, electromagnetism-like mechanism is introduced to the resampling procedure in single-robot FastSLAM, where we assume that each sampling particle is looked at as a charged electron and attraction-repulsion mechanism in electromagnetism field is used to simulate interactive force between the particles to improve the distribution of particles. Secondly, when multiple robots observe the same landmarks, every robot is regarded as one node and Kalman-Consensus Filter is proposed to update landmark information, which further improves the accuracy of localization and mapping. Finally, the simulation results show that the algorithm is suitable and effective.

scholarly journals A Review on Map-Merging Methods for Typical Map Types in Multiple-Ground-Robot SLAM Solutions

Sensors ◽  
2020 ◽  
Vol 20 (23) ◽  
pp. 6988
Author(s):  
Shuien Yu ◽  
Chunyun Fu ◽  
Amirali K. Gostar ◽  
Minghui Hu
Keyword(s):  
Multiple Robots ◽  
Working Mechanism ◽  
Topological Maps ◽  
Occupancy Grid ◽  
Localization And Mapping ◽  
Robot Systems ◽  
Feature Based ◽  
Occupancy Grid Maps ◽  
Multi Robot ◽  
Map Merging

When multiple robots are involved in the process of simultaneous localization and mapping (SLAM), a global map should be constructed by merging the local maps built by individual robots, so as to provide a better representation of the environment. Hence, the map-merging methods play a crucial rule in multi-robot systems and determine the performance of multi-robot SLAM. This paper looks into the key problem of map merging for multiple-ground-robot SLAM and reviews the typical map-merging methods for several important types of maps in SLAM applications: occupancy grid maps, feature-based maps, and topological maps. These map-merging approaches are classified based on their working mechanism or the type of features they deal with. The concepts and characteristics of these map-merging methods are elaborated in this review. The contents summarized in this paper provide insights and guidance for future multiple-ground-robot SLAM solutions.

Collision-free trajectory control for multiple robots based on neural optimization network

Robotica ◽  
1990 ◽  
Vol 8 (3) ◽  
pp. 185-194 ◽  
Author(s):  
Jihong Lee ◽  
Zeungnam Bien
Keyword(s):  
Differential Equation ◽  
Mobile Robots ◽  
Neural Circuit ◽  
Heuristic Method ◽  
Trajectory Control ◽  
New Method ◽  
Multiple Robots ◽  
Simulation Results ◽  
Articulated Robot ◽  
Neural Optimization

SUMMARYA collision-free trajectory control for multiple robots is proposed. The proposed method is based on the concept of neural optimization network. The positions or configurations of robots are taken as the variables of the neural circuit, and the energy of network is determined by combining various functions, in which one function is to make each robot approach to its goal and another helps each robot from colliding with other robots or obstacles. Also a differential equation of the circuit which tends to minimize the energy is derived. A new method for describing collision between articulated arms is presented and some heuristic method to improve the feasibility and the safety of the trajectory is proposed. Also illustrative simulation results for mobile robots and articulated robot arms are presented.

Cooperative Towing With Multiple Robots

2008 ◽  
Author(s):  
Jonathan Fink ◽  
Peng Cheng ◽  
Vijay Kumar
Keyword(s):  
Mobile Robots ◽  
Dry Friction ◽  
Equations Of Motion ◽  
Static Model ◽  
Multiple Robots ◽  
Coordinated Motion ◽  
Multiple Mobile Robots ◽  
Basic Concepts ◽  
Simulation Results

In this paper, we address the cooperative towing of payloads by multiple mobile robots in the plane. Robots are attached via cables to a planar object or a pallet carrying a payload. Coordinated motion by the robots allow the payload to be manipulated through a planar, warehouse-like environment. We formulate a quasi-static model for manipulation and derive equations of motion that yield the motion of the payload for a prescribed motion of the robots in the presence of dry friction and tension constraints. We present experimental and simulation results that demonstrate the basic concepts.

scholarly journals Developing a real time navigation for the mobile robots at unknown environments

2020 ◽  
Vol 20 (1) ◽  
pp. 500
Author(s):  
Sarah Haider Abdulredah ◽  
Dheyaa Jasim Kadhim
Keyword(s):  
Mobile Robot ◽  
Mean Square ◽  
Matlab Simulation ◽  
Robot Operating System ◽  
Unknown Environments ◽  
Localization And Mapping ◽  
Software Platforms ◽  
The Mean ◽  
Simulation Results ◽  
Robot Platform

<p><span>This research deals with the feasibility of a mobile robot to navigate and discover its location at unknown environments, and then constructing maps of these navigated environments for future usage. In this work, we proposed a modified Extended Kalman Filter- Simultaneous Localization and Mapping (EKF-SLAM) technique which was implemented for different unknown environments containing a different number of landmarks. Then, the detectable landmarks will play an important role in controlling the overall navigation process and EKF-SLAM technique’s performance. MATLAB simulation results of the EKF-SLAM technique come with better performance as compared with an odometry approach performance in terms of measuring the mean square error, especially when increasing the number of landmarks. After that, we simulate and evaluate a mobile robot platform named TurtleBot2e in Gazebo simulator software to achieve the using of the SLAM technique for a different environment using the Rviz library which was built on Robot Operating System in Linux. The main conclusion comes with this work is the simulation and implementation of the SLAM technique using two software platforms separately (MATLAB and ROS) in different unknown environments containing a different number of landmarks so a few number of landmark will make the mobile robot loses its path.</span></p>

scholarly journals A hypothesis of state covariance decorrelation effects to partial observability SLAM

2019 ◽  
Vol 14 (2) ◽  
pp. 588 ◽  
Author(s):  
H Ahmad ◽  
N.A Othman ◽  
M M Saari ◽  
M S Ramli ◽  
M M Mazlan ◽  
...  
Keyword(s):  
Kalman Filter ◽  
Extended Kalman Filter ◽  
Matrix Inversion ◽  
Matrix Norm ◽  
Main Element ◽  
Partial Observability ◽  
Localization And Mapping ◽  
The Matrix ◽  
Simulation Results ◽  
Partially Observable

<span>This paper analyze the performance of partial observability in simultaneous localization and mapping(SLAM) problem. The study focuses mainly on the effect of having a decorrelation technique known as Covariance Inflation to the estimation. The matrix inversion will be the main element to be investigated through two conditions with respect to some defined environment namely as unstable partially observable SLAM and partially observable SLAM via matrix norm analysis. For assessment purposes, the Extended Kalman Filter estimation is referred as the estimator to understand how the conditions can influence the results. The simulation results depicted that, the matrix norm is able to determine the efficiency of estimation and is proportional to the uncertainties of the system.</span>

UAV Active SLAM Trajectory Programming Based on Optimal Control

2013 ◽  
Vol 765-767 ◽  
pp. 1932-1935
Author(s):  
Zeng Xiang Yang ◽  
Sai Jin
Keyword(s):  
Optimal Control ◽  
Optimization Problem ◽  
Simultaneous Localization And Mapping ◽  
Plane Motion ◽  
Programming Algorithm ◽  
Motion Model ◽  
Unknown Environment ◽  
Localization And Mapping ◽  
Simulation Results ◽  
Slam Algorithm

To decrease the uncertainty of simultaneous localization and mapping of UAV, and at the same time, to increase the speed of searching the unknown environment at which UAV locates, an active SLAM trajectory programming algorithm is proposed based on optimal control. Therefore, UAV SLAM is tackled as a combined optimization problem, considering the precision of UAV location and mapping integrity. Based on the simplified UAV plane motion model, this algorithm is simulated and tested by comparing with the random SLAM algorithm. Simulation results show that this algorithm is effective.

scholarly journals Consensus-Based Filter for Distributed Sensor Networks with Colored Measurement Noise

Sensors ◽  
2018 ◽  
Vol 18 (11) ◽  
pp. 3678 ◽  
Author(s):  
Jinran Wang ◽  
Peng Dong ◽  
Zhongliang Jing ◽  
Jin Cheng
Keyword(s):  
Sensor Networks ◽  
The State ◽  
Measurement Noise ◽  
Distributed Sensor Networks ◽  
Distributed Sensor ◽  
Distributed State Estimation ◽  
Consensus Filter ◽  
Simulation Results ◽  
Augmented State ◽  
Distributed Filter

Consensus filtering is an effective method for distributed state estimation of distributed sensor networks and the assumption of white measurement noise is widely used. However, when the measurement noise is colored, the traditional consensus filter cannot work well. In this paper, we first propose a consensus-based distributed filter for colored measurement noise by augmenting the state to include the colored measurement noise. To improve the efficiency of the filter, only local colored measurement noise is integrated into the augmented state for each local filter. Furthermore, another consensus-based distributed filter based on measurement differencing scheme is developed to eliminate the ill-conditioned computations of the augmented state approach. In addition, this method does not need to augment the state and thus has lower dimension than the augmented state filter. Simulation results demonstrate the superiority of the proposed methods.

scholarly journals 5G SLAM Using the Clustering and Assignment Approach with Diffuse Multipath

Sensors ◽  
2020 ◽  
Vol 20 (16) ◽  
pp. 4656 ◽  
Author(s):  
Yu Ge ◽  
Fuxi Wen ◽  
Hyowon Kim ◽  
Meifang Zhu ◽  
Fan Jiang ◽  
...  
Keyword(s):  
Data Transmission ◽  
Communication Systems ◽  
Likelihood Function ◽  
Signal Propagation ◽  
Localization And Mapping ◽  
Channel Parameter ◽  
Lower Complexity ◽  
Simulation Results ◽  
24 Ghz ◽  
Assignment Approach

5G communication systems operating above 24 GHz have promising properties for user localization and environment mapping. Existing studies have either relied on simplified abstract models of the signal propagation and the measurements, or are based on direct positioning approaches, which directly map the received waveform to a position. In this study, we consider an intermediate approach, which consists of four phases—downlink data transmission, multi-dimensional channel estimation, channel parameter clustering, and simultaneous localization and mapping (SLAM) based on a novel likelihood function. This approach can decompose the problem into simpler steps, thus leading to lower complexity. At the same time, by considering an end-to-end processing chain, we are accounting for a wide variety of practical impairments. Simulation results demonstrate the efficacy of the proposed approach.

Research on Cooperation Localization and Mapping for Hoisting Multi-Robot System

2012 ◽  
Vol 229-231 ◽  
pp. 2248-2252
Author(s):  
Lin Jun ◽  
Zi Bin ◽  
Wu Xia
Keyword(s):  
Mobile Robots ◽  
Grid Method ◽  
Sensor Technology ◽  
Robot System ◽  
Localization And Mapping ◽  
Practical Operation ◽  
Mapping System ◽  
Simulation Results ◽  
Multiple Robot ◽  
Multi Robot

According to the practical operation of the hoisting multi-mobile robots system (HMRS), the cooperation localization and mapping is studied. Firstly, an improved algorithm of cooperation localization solution of multiple robot system is proposed based on map gridding algorithm. In addition, by virtue of sensor technology, the grid method is designed, which has the ability of accurate, reliable localization and rapid local mapping of the HMRS. Finally, simulation results demonstrate that the localization and mapping system is feasible and efficient.

Active exploration using a scheme for autonomous allocation of landmarks

Robotica ◽  
2013 ◽  
Vol 32 (5) ◽  
pp. 757-782 ◽  
Author(s):  
Jing Yuan ◽  
Yalou Huang ◽  
Fengchi Sun ◽  
Tong Tao
Keyword(s):  
Optimization Problem ◽  
Polar Regions ◽  
Multi Objective Optimization ◽  
Heuristic Rules ◽  
Redundancy Elimination ◽  
Accurate Localization ◽  
Localization And Mapping ◽  
On Line ◽  
Simulation Results ◽  
Active Exploration

SUMMARYIn this paper, we focus on the unknown environments without artificial landmarks and features, such as disaster situations and polar regions. An approach to active exploration based on an on-line scheme for autonomous allocation of landmarks is proposed. Specifically, the robot carries along with itself some landmarks which are to be allocated during the exploration according to some heuristic rules. The utility of landmark allocation is analyzed and calculated. Then the active exploration is converted into a problem of multi-objective optimization. The objective function includes three weighted terms: the accuracy of localization and mapping, the coverage rate of the unknown environment and the utility of the allocated landmarks. By solving this optimization problem, control inputs of the robot are computed to guarantee that accurate localization, high-quality mapping and complete exploration can be achieved simultaneously. Moreover, supplementation and redundancy elimination of the allocated landmarks are executed to make a complete and non-redundant coverage for the environment. Finally, some landmarks, together with a device for allocating these landmarks, are developed. Both experiment and simulation results are presented to demonstrate the effectiveness of the proposed approach.

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