Special Issue "Modeling, Control, and Applications of Field Robotics"

A special issue of Electronics (ISSN 2079-9292). This special issue belongs to the section "Systems & Control Engineering".

Deadline for manuscript submissions: 30 November 2020.

Special Issue Editors

Prof. Dr. Hyoung Il Son
Website
Guest Editor
Department of Rural and Biosystems Engineering and Department of Robotics Engineering Convergence, Chonnam National University, 88 Yongbong-ro, Buk-gu, Gwangju 81186, Korea
Interests: field robotics; hybrid systems; agricultural robotics; teleoperation; haptics
Prof. Dr. Myun Joong Hwang
Website
Guest Editor
Department of Mechanical Engineering, Korea National University of Transportation, 50 Daehak-ro, Chungju-si, Chungbuk 27469, Korea
Interests: robot motion and control; field robotics; robotic manipulation; autonomous systems

Special Issue Information

Dear Colleagues,

Field robotics is concerned with the automation of vehicles and platforms to assist and/or replace humans performing tasks that are difficult, repetitive, unpleasant, or operate in harsh, unstructured environments. Field robotics encompasses the automation of many land, sea, and air platforms in applications such as agriculture, construction, mining, forestry, unban, underwater, military, and space. Field robotics is characterized by the application of the most advanced robotics principles in sensing, perception, control, and reasoning in unstructured and unknown environments. The appeal of field robotics is that it is challenging science, involves the latest engineering and systems design principles, and offers the real prospect of robotic principles making a substantial economic and social contribution to many different application areas. Recently, multi-robot systems has also become one of the main topics in the field to cover large-scale outdoor environments.

This Special Issue focuses on design, modeling, and control techniques for field robotics and possible applications of those results to give a large and complete view of complex research issues. We plan to invite a series of research results that span theoretical, design, and applied topics such as building robust field robots, (heterogeneous) multi-robot teams, environmental monitoring, and active robotic sensing and sampling.

Submissions to this Special Issue on ‘Modeling, Control, and Applications of Field Robotics’’ are solicited to represent a snapshot of the field’s development by covering a range of topics that include but are not limited to new methods, algorithms, solutions, and applications in the following areas:

  • Design of robotic systems for challenging field applications
  • Novel perceptions of field robots including passive and active methods
  • Mobile manipulators for active sensing and sampling
  • Long-term autonomy and navigation in unstructured environments
  • Data analytics and real-time decision making
  • Low-cost sensing and algorithms for full-day operations
  • Human user interfaces
  • Multi-robot coordination
  • Sensor networks
  • Large-scale mapping
  • Field robotics applications: agriculture, construction, mining, forestry, urban, underwater, military, space, and etc

Prof. Dr. Hyoung Il Son
Prof. Dr. Myun Joong Hwang
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All papers will be peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Electronics is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • Mobile robotics
  • Aerial robotics
  • Localization and mapping
  • Perception
  • Planning
  • Coordination
  • Control
  • Sensing
  • Monitoring
  • Sampling
  • Exploration
  • Surveillance and rescue
  • Agricultural robotics
  • Construction robotics
  • Underwater robotics
  • Marine robotics
  • Space robotics
  • Military robotics
  • Multi-robot systems
  • Heterogeneous robotics

Published Papers (2 papers)

Order results
Result details
Select all
Export citation of selected articles as:

Research

Open AccessArticle
A Multi-Objective Trajectory Planning Method for Collaborative Robot
Electronics 2020, 9(5), 859; https://doi.org/10.3390/electronics9050859 - 22 May 2020
Abstract
Aiming at the characteristics of high efficiency and smoothness in the motion process of collaborative robot, a multi-objective trajectory planning method is proposed. Firstly, the kinematics model of the collaborative robot is established, and the trajectory in the workspace is converted into joint [...] Read more.
Aiming at the characteristics of high efficiency and smoothness in the motion process of collaborative robot, a multi-objective trajectory planning method is proposed. Firstly, the kinematics model of the collaborative robot is established, and the trajectory in the workspace is converted into joint space trajectory using inverse kinematics method. Secondly, seven-order B-spline functions are used to construct joint trajectory sequences to ensure the continuous position, velocity, acceleration and jerk of each joint. Then, the trajectory competitive multi-objective particle swarm optimization (TCMOPSO) algorithm is proposed to search the Pareto optimal solutions set of the robot’s time-energy-jerk optimal trajectory. Further, the normalized weight function is proposed to select the appropriate solution. Finally, the algorithm simulation experiment is completed in MATLAB, and the robot control experiment is completed using the Robot Operating System (ROS). The experimental results show that the method can achieve effective multi-objective optimization, the appropriate optimal trajectory can be obtained according to the actual requirements, and the collaborative robot is actually operating well. Full article
(This article belongs to the Special Issue Modeling, Control, and Applications of Field Robotics)
Show Figures

Figure 1

Open AccessArticle
A Novel FastSLAM Framework Based on 2D Lidar for Autonomous Mobile Robot
Electronics 2020, 9(4), 695; https://doi.org/10.3390/electronics9040695 - 24 Apr 2020
Abstract
The autonomous navigation and environment exploration of mobile robots are carried out on the premise of the ability of environment sensing. Simultaneous localisation and mapping (SLAM) is the key algorithm in perceiving and mapping an environment in real time. FastSLAM has played an [...] Read more.
The autonomous navigation and environment exploration of mobile robots are carried out on the premise of the ability of environment sensing. Simultaneous localisation and mapping (SLAM) is the key algorithm in perceiving and mapping an environment in real time. FastSLAM has played an increasingly significant role in the SLAM problem. In order to enhance the performance of FastSLAM, a novel framework called IFastSLAM is proposed, based on particle swarm optimisation (PSO). In this framework, an adaptive resampling strategy is proposed that uses the genetic algorithm to increase the diversity of particles, and the principles of fractional differential theory and chaotic optimisation are combined into the algorithm to improve the conventional PSO approach. We observe that the fractional differential approach speeds up the iteration of the algorithm and chaotic optimisation prevents premature convergence. A new idea of a virtual particle is put forward as the global optimisation target for the improved PSO scheme. This approach is more accurate in terms of determining the optimisation target based on the geometric position of the particle, compared to an approach based on the maximum weight value of the particle. The proposed IFastSLAM method is compared with conventional FastSLAM, PSO-FastSLAM, and an adaptive generic FastSLAM algorithm (AGA-FastSLAM). The superiority of IFastSLAM is verified by simulations, experiments with a real-world dataset, and field experiments. Full article
(This article belongs to the Special Issue Modeling, Control, and Applications of Field Robotics)
Show Figures

Figure 1

Back to TopTop