Special Issue "Mobile Robotics and Autonomous Intelligent Systems"

A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Robotics and Automation".

Deadline for manuscript submissions: 20 May 2024 | Viewed by 10728

Special Issue Editors

Department of Control Science and Engineering, Harbin Institute of Technology, Harbin 150001, China
Interests: autonomous unmanned vehicles; multi-robot task planning and control; autonomous decision-making of unmanned systems; multiagent control systems
Department of Control Science and Engineering, Harbin Institute of Technology, Harbin 150001, China
Interests: analysis and design for complex dynamical systems; signal processing; optimization techniques and applications; sliding mode control; intelligent systems and robot technology; machine vision and intelligent detection technology; advanced control techniques for power electronic systems; aircraft control
School of Automation, Chongqing University, Chongqing 400030, China
Interests: intelligent systems and control; intelligent robotics; signal processing (digital filter design, signal processing for uncertain systems, robust and optimal filtering)

Special Issue Information

Dear Colleagues,

The rapid development of robotic systems and intelligent systems has brought tremendous changes to energy, transportation, medicine, manufacturing, agriculture, and other industries. Advanced mobile robotics and autonomous intelligent systems are now key technologies in aerospace, scientific exploration, security, disaster relief, etc.

In the field of mobile robotics and autonomous intelligent systems, new methods of perception, decision, and control have been constant hot topics involving multi-input multi-output, high nonlinearity, strong coupling, and uncertainties. Stability, flexibility, scalability, robustness, safety, and efficiency are also crucial to effective robotic and intelligent systems and remain issues that must be addressed.

This Special Issue, entitled “Mobile Robotics and Autonomous Intelligent Systems,” will present the latest trends in automation technology, robotics, and artificial intelligence and discuss the present advances and challenges in mobile robotic systems and intelligent systems. With this aim in mind, we are seeking innovative research on perception, decision making, task planning, and control.

Review articles and original research articles are welcome. Topics of interests include, but are not limited to, the following:

  • Motion control and motion planning for intelligent vehicles;
  • Task planning, path planning, and trajectory generation for mobile robotics;
  • Robotic task decomposition, allocations and scheduling;
  • Simultaneous localization and mapping in a complex environment;
  • Active disturbance rejection control for robotics;
  • Dexterous manipulation for robotic systems;
  • Model-based predictive control for intelligent systems;
  • Robust control, sliding mode control, and adaptive control for robotic systems;
  • Deep learning and reinforcement learning for mobile robotics;
  • Optimization and optimal control for robotic systems;
  • Advanced decision and control methods for unmanned systems;
  • Architecture for robotic and intelligent systems.

We look forward to receiving your contributions.

Dr. Weiran Yao
Prof. Dr. Ligang Wu
Prof. Dr. Xiaojie Su
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 submissions that pass pre-check are 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. Applied Sciences is an international peer-reviewed open access semimonthly 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 2300 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 robotic systems
  • intelligent systems
  • autonomous unmanned systems
  • task planning
  • motion planning and control
  • robust and secure control
  • intelligent control
  • perception and cognition
  • optimization

Published Papers (8 papers)

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

Research

18 pages, 10943 KiB  
Article
Path Planning of Rail-Mounted Logistics Robots Based on the Improved Dijkstra Algorithm
Appl. Sci. 2023, 13(17), 9955; https://doi.org/10.3390/app13179955 - 03 Sep 2023
Cited by 1 | Viewed by 643
Abstract
With the upgrading of manufacturing production lines and innovations in information technology, logistics robot technology applied in factories is maturing. Rail-mounted logistics robots are suitable for precise material distribution in large production workshops with fixed routes and over long distances. However, designing an [...] Read more.
With the upgrading of manufacturing production lines and innovations in information technology, logistics robot technology applied in factories is maturing. Rail-mounted logistics robots are suitable for precise material distribution in large production workshops with fixed routes and over long distances. However, designing an efficient path-planning algorithm is the key to realizing high efficiency in multi-robot system operations with rail logistics. Therefore, this paper proposes an improved Dijkstra algorithm that introduces real-time node occupancy and a time window conflict judgment model for global path planning and conflict coordination in multi-robot systems. More specifically, the introduction of real-time node occupancy can determine the shortest feasible routes for each task, and the introduction of the time window conflict judgment model can avoid the route conflict problem in the execution of multiple tasks, planning the shortest route without conflict. For the robot UBW positioning module, a Chan algorithm based on TDOA is proposed to realize the accurate positioning of rail-mounted logistics robots during their operation. Compared with the traditional Dijkstra algorithm, the results show that the algorithm proposed herein can plan a conflict-free and better path and dynamically adjust the on-orbit conflict in real time to avoid track congestion and efficiently complete multiple distribution tasks. Full article
(This article belongs to the Special Issue Mobile Robotics and Autonomous Intelligent Systems)
Show Figures

Figure 1

13 pages, 4394 KiB  
Article
Study on Head Stabilization Control Strategy of Non-Wheeled Snake Robot Based on Inertial Sensor
Appl. Sci. 2023, 13(7), 4477; https://doi.org/10.3390/app13074477 - 31 Mar 2023
Viewed by 818
Abstract
In this paper, the head stabilization problem of the snake robot in planar motion is studied. When the snake robot performs a planar movement with an inchworm locomotion gait, the head controller of the snake robot swings up and down due to a [...] Read more.
In this paper, the head stabilization problem of the snake robot in planar motion is studied. When the snake robot performs a planar movement with an inchworm locomotion gait, the head controller of the snake robot swings up and down due to a fluctuation in the joint angle of the neck joint. However, the snake robot usually has a laser radar and other visual instruments on the head, and the swing of the head causes the visual instrument to fail to obtain external visual information normally, which affects the navigation and detection of the snake robot. In this paper, a head stabilization method for a snake robot in planar motion is proposed. The inertial sensor is used to obtain the direction parameters to control the swing of the head when the snake robot moves, and the effectiveness of the method is verified by a simulation and an experiment of the real robot. Full article
(This article belongs to the Special Issue Mobile Robotics and Autonomous Intelligent Systems)
Show Figures

Figure 1

12 pages, 968 KiB  
Article
Learning Form Closure Grasping with a Four-Pin Parallel Gripper
Appl. Sci. 2023, 13(4), 2506; https://doi.org/10.3390/app13042506 - 15 Feb 2023
Cited by 1 | Viewed by 820
Abstract
Being able to stably grasp with generalization is one of the distinguished capabilities for building a generic grasping system for robots. In this work, we propose a stable grasping method for four-pin parallel grippers within a reinforcement learning framework. First, a reinforcement learning [...] Read more.
Being able to stably grasp with generalization is one of the distinguished capabilities for building a generic grasping system for robots. In this work, we propose a stable grasping method for four-pin parallel grippers within a reinforcement learning framework. First, a reinforcement learning problem is constructed on the basis of the improved four-pin gripper. Then, the learning policy and the reward function are constructed in consideration of the knowledge of environmental constraint and form closure. Finally, the effectiveness of the designed grasping method is validated in a simulated environment, and the results demonstrate that a safe and stable grasp can be planned for given 2.5D objects. Full article
(This article belongs to the Special Issue Mobile Robotics and Autonomous Intelligent Systems)
Show Figures

Figure 1

12 pages, 1886 KiB  
Article
Underground Garage Patrol Based on Road Marking Recognition by Keras and Tensorflow
Appl. Sci. 2023, 13(4), 2385; https://doi.org/10.3390/app13042385 - 13 Feb 2023
Viewed by 1137
Abstract
The purpose of this study was to design an unmanned patrol service in combination with artificial intelligence technology to solve the problem of underground vehicle patrol. This design used the Raspberry Pi development board, L298N driver chip, Raspberry Pi camera, and other major [...] Read more.
The purpose of this study was to design an unmanned patrol service in combination with artificial intelligence technology to solve the problem of underground vehicle patrol. This design used the Raspberry Pi development board, L298N driver chip, Raspberry Pi camera, and other major hardware equipment to transform the remote control car. This design used Python as the programming language. By writing Python code, the car could be driven under the control of the computer keyboard and the camera was turned on for data collection. The Keras neural network library was used to quickly build a neural network model, the collected data was used to train the model, and the model was finally generated. The model was placed in the TensorFlow system for processing, and the car could travel in a preset track for unmanned driving. Full article
(This article belongs to the Special Issue Mobile Robotics and Autonomous Intelligent Systems)
Show Figures

Figure 1

17 pages, 3693 KiB  
Article
Autonomous Visual Navigation System Based on a Single Camera for Floor-Sweeping Robot
Appl. Sci. 2023, 13(3), 1562; https://doi.org/10.3390/app13031562 - 25 Jan 2023
Cited by 1 | Viewed by 1809
Abstract
The indoor sweeping robot industry has developed rapidly in recent years. The current sweeping robot environment perception sensor configuration is more diverse and generally does not have active garbage detection capabilities. Advances in computer vision technology, artificial intelligence, and cloud computing technology have [...] Read more.
The indoor sweeping robot industry has developed rapidly in recent years. The current sweeping robot environment perception sensor configuration is more diverse and generally does not have active garbage detection capabilities. Advances in computer vision technology, artificial intelligence, and cloud computing technology have provided new possibilities for the development of sweeping robot technology. This paper conceptualizes a new autonomous visual navigation system based on a single-camera sensor for floor-sweeping robots. It investigates critical technologies such as floor litter recognition, environmental perception, and dynamic local path planning based on depth maps. The system is applied to the TurtleBot robot for experiments, and the results show that the mAP accuracy of the autonomous visual navigation system for fine trash recognition is 91.28%; it reduces the average relative error of depth perception by 10.4% compared to conventional methods. Moreover, it has greatly improved the dynamics and immediacy of path planning. Full article
(This article belongs to the Special Issue Mobile Robotics and Autonomous Intelligent Systems)
Show Figures

Figure 1

14 pages, 1003 KiB  
Article
Leader-Following Formation Tracking Control of Nonholonomic Mobile Robots Considering Collision Avoidance: A System Transformation Approach
Appl. Sci. 2022, 12(24), 12579; https://doi.org/10.3390/app122412579 - 08 Dec 2022
Viewed by 853
Abstract
In this paper, the obstacle avoidance problem-based leader–following formation tracking of nonholonomic wheeled mobile robots with unknown parameters of desired trajectory is investigated. First, the under-actuated system is transformed into a fully-actuated system by obtaining an auxiliary control variable using the transverse function. [...] Read more.
In this paper, the obstacle avoidance problem-based leader–following formation tracking of nonholonomic wheeled mobile robots with unknown parameters of desired trajectory is investigated. First, the under-actuated system is transformed into a fully-actuated system by obtaining an auxiliary control variable using the transverse function. Second, by introducing a potential function for each obstacle, the influence of obstacles is considered in trajectory tracking, and the effect of the potential field on mobile robots is taken into account in the system tracking error. Third, the adaptive laws are designed to estimate the unknown parameters of the desired trajectory. Fourth, the results show that the formation error with respect to the actual position and orientation can be arbitrarily small by selecting appropriate design parameters. Finally, simulation examples are used to demonstrate that the proposed control scheme is effective. Full article
(This article belongs to the Special Issue Mobile Robotics and Autonomous Intelligent Systems)
Show Figures

Figure 1

14 pages, 2349 KiB  
Article
Temporal Logic Planning and Receding Horizon Control for Signal Source Localization
Appl. Sci. 2022, 12(21), 10984; https://doi.org/10.3390/app122110984 - 30 Oct 2022
Viewed by 727
Abstract
This article copes with signal source localization by employing a receding horizon control approach with temporal logic planning in the light of a single mobile robot. First, a temporal logic planning approach is proposed such that the task requirements from the temporal logic [...] Read more.
This article copes with signal source localization by employing a receding horizon control approach with temporal logic planning in the light of a single mobile robot. First, a temporal logic planning approach is proposed such that the task requirements from the temporal logic specifications can be effectively dealt with based on the product automaton in an offline fashion. Second, in order to label the key nodes of the product automaton, a particle filter is utilized to predict the source positions as the key nodes. Third, on the basis of the product automaton, a receding horizon control approach with temporal logic planning is developed to produce the robot’s trajectory that satisfies a given linear temporal logic specification. Finally, the effectiveness of the proposed control approach is illustrated for signal source localization. Full article
(This article belongs to the Special Issue Mobile Robotics and Autonomous Intelligent Systems)
Show Figures

Figure 1

19 pages, 7441 KiB  
Article
Recognition and Location Algorithm for Pallets in Warehouses Using RGB-D Sensor
Appl. Sci. 2022, 12(20), 10331; https://doi.org/10.3390/app122010331 - 13 Oct 2022
Cited by 1 | Viewed by 1773
Abstract
(1) Background: Forklifts are used widely in factories, but it shows the problem of large uncertainties when using an RGB-D sensor to recognize and locate pallets in warehouse environments. To enhance the flexibility of current autonomous forklifts in unstructured environments, the improved labeled [...] Read more.
(1) Background: Forklifts are used widely in factories, but it shows the problem of large uncertainties when using an RGB-D sensor to recognize and locate pallets in warehouse environments. To enhance the flexibility of current autonomous forklifts in unstructured environments, the improved labeled template matching algorithm was proposed to recognize pallets. (2) Methods: The algorithm comprises four steps: (i) classifying each pixel of a color image with the color feature and obtaining the category matrix; (ii) building a labeled template containing the goods, pallet, and ground category information; (iii) compressing and matching the category matrix and template to determine the region of the pallet; and (iv) extracting the pallet pose from information in respect of the pallet feet. (3) Results: The results show that the proposed algorithm is robust against environmental influences and obstacles and that it can precisely recognize and segment multiple pallets in a warehouse with a 92.6% detection rate. The time consumptions were 72.44, 85.45, 117.63, and 182.84 ms for detection distances of 1000, 2000, 3000, and 4000 mm, respectively. (4) Conclusions: Both static and dynamic experiments were conducted, and the results demonstrate that the detection accuracy is directly related to the detection angle and distance. Full article
(This article belongs to the Special Issue Mobile Robotics and Autonomous Intelligent Systems)
Show Figures

Figure 1

Back to TopTop