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Trajectory Analysis, Positioning and Control of Mobile Robots

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

Deadline for manuscript submissions: closed (29 February 2024) | Viewed by 19898

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Dr. J. Ernesto Solanes

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Department of Systems Engineering and Automation, Universidad Politécnica de Valencia UPV, 46022 València, Spain
Interests: human–robot interaction; robotics; nonlinear and robust control; computer vision
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Prof. Dr. Luis Gracia

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Guest Editor

Instituto IDF, Universitat Politecnica de Valencia, 46022 Valencia, Spain
Interests: robotic systems; system modeling and control; robust control
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Dear Colleagues,

In the last decade, mobile robots have increased their presence in our society. It is becoming increasingly common to read about self-driving cars, robots utilized for quality control or dangerous tasks, and drones used for product delivery. The improvements made in the fields of computer science, electronics, and power technologies, together with advances in artificial intelligence (AI), SLAM, navigation, and control of dynamic systems, are providing mobile robots with greater robustness and new capabilities to adapt themselves to the environment uncertainties.

In addition to the classical problems in mobile robotics, their presence alongside humans gives rise to problems derived from the interaction between humans and robotic systems. Today, there is a need to develop new science in the mobile robotics field to overcome the human–mobile robot interaction problem.

The emergence of new human–machine interaction tools based on augmented reality (AR) or virtual reality (VR), together with advances in AI, SLAM, navigation, and control, opens new possibilities to be analyzed in the field of mobile robotics.

The aim of this Special Issue on “Trajectory Analysis, Positioning and Control of Mobile Robots” is to provide an overview of this wide field. It should be of interest to the artificial intelligence, robotics, control, augmented, and virtual reality communities. Therefore, this Special Issue welcomes the submission of technical, experimental, and methodological papers related to artificial intelligence, navigation, SLAM, control theory, and human–robot interaction applied to mobile robotics.

Dr. J. Ernesto Solanes
Prof. Dr. Luis Gracia
Guest Editors

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Keywords

mobile robots
trajectory planning
obstacle avoidance
navigation
SLAM
artificial intelligence
neural networks
deep learning
robot control
augmented reality
virtual reality
human–robot interaction

Published Papers (9 papers)

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Research

19 pages, 8013 KiB

Open AccessArticle

A Spatial Location Representation Method Incorporating Boundary Information

by Hui Jiang and Yukun Zhang

Appl. Sci. 2023, 13(13), 7929; https://doi.org/10.3390/app13137929 - 06 Jul 2023

Cited by 1 | Viewed by 729

Abstract

In response to problems concerning the low autonomous localization accuracy of mobile robots in unknown environments and large cumulative errors due to long time running, a spatial location representation method incorporating boundary information (SLRB) is proposed, inspired by the mammalian spatial cognitive mechanism. In modeling the firing characteristics of boundary cells to environmental boundary information, we construct vector relationships between the mobile robot and environmental boundaries with direction-aware information and distance-aware information. The self-motion information (direction and velocity) is used as the input to the lateral anti-Hebbian network (LAHN) to generate grid cells. In addition, the boundary cell response values are used to update the grid cell distribution law and to suppress the error response of the place cells, thus reducing the localization error of the mobile robot. Meanwhile, when the mobile robot reaches the boundary cell excitation zone, the activated boundary cells are used to correct the accumulated errors that occur due to long running times, which thus improves the localization accuracy of the system. The main contributions of this paper are as follows: 1. We propose a novel method for constructing boundary cell models. 2. An approach is presented that maps the response values of boundary cells to the input layer of LAHN (Location-Adaptive Hierarchical Network), where grid cells are generated through LAHN learning rules, and the distribution pattern of grid cells is adjusted using the response values of boundary cells. 3. We correct the cumulative error caused by long-term operation of place cells through the activation of boundary cells, ensuring that only one place cell responds to the current location at each individual moment, thereby improving the positioning accuracy of the system. Full article

(This article belongs to the Special Issue Trajectory Analysis, Positioning and Control of Mobile Robots)

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22 pages, 44868 KiB

Open AccessArticle

Point–Line-Aware Heterogeneous Graph Attention Network for Visual SLAM System

by Yuanfeng Lian, Hao Sun and Shaohua Dong

Appl. Sci. 2023, 13(6), 3816; https://doi.org/10.3390/app13063816 - 16 Mar 2023

Viewed by 1495

Abstract

Simultaneous localization and mapping (SLAM), as an important research topic in robotics, is useful but challenging to estimate robot pose and reconstruct a 3-D map of the surrounding environment. Despite recent success of several deep neural networks for visual SLAM, those methods cannot achieve robust results in complex industrial scenarios for constructing accurate and real-time maps due to the weak texture and complex geometric structure. This paper presents a novel and efficient visual SLAM system based on point–line-aware heterogeneous graph attention network, which combines points and line segments to solve the problem of the insufficient number of reliable features in traditional approaches. Firstly, a simultaneous feature extraction network is constructed based on the geometric relationships between points and points and points and lines. To further improve the efficiency and accuracy of the geometric association features of key regions, we design the point–line-aware attention module to guide the network to pay attention to the trivial features of both points and lines in images. Moreover, the network model is optimized by a transfer-aware knowledge distillation strategy to further improve the system’s real-time performance. Secondly, to improve the accuracy of the point–line matching, we design a point–line heterogeneous graph attention network, which combines an edge aggregation graph attention module and a cross-heterogeneous graph iteration module to conduct learning on the intragraph and intergraph. Finally, the point–line matching process is transformed into an optimal transport problem, and a near-iterative method based on a greedy strategy is presented to solve the optimization problem. The experiments on the KITTI dataset and a self-made dataset demonstrate the better effectiveness, accuracy, and adaptability of our method than those of the state of the art in visual SLAM. Full article

(This article belongs to the Special Issue Trajectory Analysis, Positioning and Control of Mobile Robots)

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13 pages, 3215 KiB

Open AccessArticle

Real-Time Stereo Visual Odometry Based on an Improved KLT Method

by Guangzhi Guo, Zuoxiao Dai and Yuanfeng Dai

Appl. Sci. 2022, 12(23), 12124; https://doi.org/10.3390/app122312124 - 27 Nov 2022

Cited by 1 | Viewed by 1013

Abstract

Real-time stereo visual odometry (SVO) localization is a challenging problem, especially for a mobile platform without parallel computing capability. A possible solution is to reduce the computational complexity of SVO using a Kanade–Lucas–Tomasi (KLT) feature tracker. However, the standard KLT is susceptible to scale distortion and affine transformation. Therefore, this work presents a novel SVO algorithm yielding robust and real-time localization based on an improved KLT method. First, in order to improve real-time performance, feature inheritance is applied to avoid time-consuming feature detection and matching processes as much as possible. Furthermore, a joint adaptive function with respect to the average disparity, translation velocity, and yaw angle is proposed to determine a suitable window size for the adaptive KLT tracker. Then, combining the standard KLT method with an epipolar constraint, a simplified KLT matcher is introduced to substitute feature-based stereo matching. Additionally, an effective veer chain matching scheme is employed to reduce the drift error. Comparative experiments on the KITTI odometry benchmark show that the proposed method achieves significant improvement in terms of time performance than the state-of-the-art single-thread approaches and strikes a better trade-off between efficiency and accuracy than the parallel SVO or multi-threaded SLAM. Full article

(This article belongs to the Special Issue Trajectory Analysis, Positioning and Control of Mobile Robots)

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19 pages, 5519 KiB

Open AccessArticle

A Comparative Study of Control Methods for X3D Quadrotor Feedback Trajectory Control

by Tanzeela Shakeel, Jehangir Arshad, Mujtaba Hussain Jaffery, Ateeq Ur Rehman, Elsayed Tag Eldin, Nivin A. Ghamry and Muhammad Shafiq

Appl. Sci. 2022, 12(18), 9254; https://doi.org/10.3390/app12189254 - 15 Sep 2022

Cited by 12 | Viewed by 1527

Abstract

Unmanned aerial vehicles (UAVs), particularly quadrotor, have seen steady growth in use over the last several decades. The quadrotor is an under-actuated nonlinear system with few actuators in comparison to the degree of freedom (DOF); hence, stabilizing its attitude and positions is a significant challenge. Furthermore, the inclusion of nonlinear dynamic factors and uncertainties makes controlling its maneuverability more challenging. The purpose of this research is to design, implement, and evaluate the effectiveness of linear and nonlinear control methods for controlling an X3D quadrotor’s intended translation position and rotation angles while hovering. The dynamics of the X3D quadrotor model were implemented in Simulink. Two linear controllers, linear quadratic regulator (LQR) and proportional integral derivate (PID), and two nonlinear controllers, fuzzy controller (FC) and model reference adaptive PID Controller (MRAPC) employing the MIT rule, were devised and implemented for the response analysis. In the MATLAB Simulink Environment, the transient performance of nonlinear and linear controllers for an X3D quadrotor is examined in terms of settling time, rising time, peak time, delay time, and overshoot. Simulation results suggest that the LQR control approach is better because of its robustness and comparatively superior performance characteristics to other controllers, particularly nonlinear controllers, listed at the same operating point, as overshoot is 0.0% and other factors are minimal for the x3D quadrotor. In addition, the LQR controller is intuitive and simple to implement. In this research, all control approaches were verified to provide adequate feedback for quadrotor stability. Full article

(This article belongs to the Special Issue Trajectory Analysis, Positioning and Control of Mobile Robots)

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20 pages, 2910 KiB

Open AccessArticle

Occupancy Reward-Driven Exploration with Deep Reinforcement Learning for Mobile Robot System

by Albina Kamalova, Suk Gyu Lee and Soon Hak Kwon

Appl. Sci. 2022, 12(18), 9249; https://doi.org/10.3390/app12189249 - 15 Sep 2022

Cited by 3 | Viewed by 1700

Abstract

This paper investigates the solution to a mobile-robot exploration problem following autonomous driving principles. The exploration task is formulated in this study as a process of building a map while a robot moves in an indoor environment beginning from full uncertainties. The sequence of robot decisions of how to move defines the strategy of the exploration that this paper aims to investigate, applying one of the Deep Reinforcement Learning methods, known as the Deep Deterministic Policy Gradient (DDPG) algorithm. A custom environment is created representing the mapping process with a map visualization, a robot model, and a reward function. The actor-critic network receives and sends input and output data, respectively, to the custom environment. The input is the data from the laser sensor, which is equipped on the robot. The output is the continuous actions of the robot in terms of linear and angular velocities. The training results of this study show the strengths and weaknesses of the DDPG algorithm for the robotic mapping problem. The implementation was developed in MATLAB platform using its corresponding toolboxes. A comparison with another exploration algorithm is also provided. Full article

(This article belongs to the Special Issue Trajectory Analysis, Positioning and Control of Mobile Robots)

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18 pages, 2790 KiB

Open AccessArticle

Implementation of Autonomous Mobile Robot in SmartFactory

by Radim Hercik, Radek Byrtus, Rene Jaros and Jiri Koziorek

Appl. Sci. 2022, 12(17), 8912; https://doi.org/10.3390/app12178912 - 05 Sep 2022

Cited by 15 | Viewed by 4355

Abstract

This study deals with the technology of autonomous mobile robots (AMR) and their implementation on the SmartFactory production line at the Technical University of Ostrava. The task of the mobile robot is to cooperate with the production line, take over the manufactured products, and then deliver them. The content also includes a description of the individual steps that were necessary to make the mobile robot operational, such as loading a virtual map of the space, creating a network for communication with the mobile robot, and programming it. The main part of the experiment deals with testing the accuracy of moving the mobile robot to each position and establishing communication between the production line and the mobile robot. A high accuracy is a necessity in this process. The result of the study is the configuration of the autonomous mobile robot. The repetitive precision of the approach of the autonomous mobile robot to a position is ±3 mm. Full article

(This article belongs to the Special Issue Trajectory Analysis, Positioning and Control of Mobile Robots)

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22 pages, 4225 KiB

Open AccessArticle

Virtual Reality-Based Interface for Advanced Assisted Mobile Robot Teleoperation

by J. Ernesto Solanes, Adolfo Muñoz, Luis Gracia and Josep Tornero

Appl. Sci. 2022, 12(12), 6071; https://doi.org/10.3390/app12126071 - 15 Jun 2022

Cited by 4 | Viewed by 2431

Abstract

This work proposes a new interface for the teleoperation of mobile robots based on virtual reality that allows a natural and intuitive interaction and cooperation between the human and the robot, which is useful for many situations, such as inspection tasks, the mapping of complex environments, etc. Contrary to previous works, the proposed interface does not seek the realism of the virtual environment but provides all the minimum necessary elements that allow the user to carry out the teleoperation task in a more natural and intuitive way. The teleoperation is carried out in such a way that the human user and the mobile robot cooperate in a synergistic way to properly accomplish the task: the user guides the robot through the environment in order to benefit from the intelligence and adaptability of the human, whereas the robot is able to automatically avoid collisions with the objects in the environment in order to benefit from its fast response. The latter is carried out using the well-known potential field-based navigation method. The efficacy of the proposed method is demonstrated through experimentation with the Turtlebot3 Burger mobile robot in both simulation and real-world scenarios. In addition, usability and presence questionnaires were also conducted with users of different ages and backgrounds to demonstrate the benefits of the proposed approach. In particular, the results of these questionnaires show that the proposed virtual reality based interface is intuitive, ergonomic and easy to use. Full article

(This article belongs to the Special Issue Trajectory Analysis, Positioning and Control of Mobile Robots)

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23 pages, 6740 KiB

Open AccessArticle

Systematic Odometry Error Evaluation and Correction in a Human-Sized Three-Wheeled Omnidirectional Mobile Robot Using Flower-Shaped Calibration Trajectories

by Jordi Palacín, Elena Rubies and Eduard Clotet

Appl. Sci. 2022, 12(5), 2606; https://doi.org/10.3390/app12052606 - 02 Mar 2022

Cited by 15 | Viewed by 3089

Abstract

Odometry is a simple and practical method that provides a periodic real-time estimation of the relative displacement of a mobile robot based on the measurement of the angular rotational speed of its wheels. The main disadvantage of odometry is its unbounded accumulation of errors, a factor that reduces the accuracy of the estimation of the absolute position and orientation of a mobile robot. This paper proposes a general procedure to evaluate and correct the systematic odometry errors of a human-sized three-wheeled omnidirectional mobile robot designed as a versatile personal assistant tool. The correction procedure is based on the definition of 36 individual calibration trajectories which together depict a flower-shaped figure, on the measurement of the odometry and ground truth trajectory of each calibration trajectory, and on the application of several strategies to iteratively adjust the effective value of the kinematic parameters of the mobile robot in order to match the estimated final position from these two trajectories. The results have shown an average improvement of 82.14% in the estimation of the final position and orientation of the mobile robot. Therefore, these results can be used for odometry calibration during the manufacturing of human-sized three-wheeled omnidirectional mobile robots. Full article

(This article belongs to the Special Issue Trajectory Analysis, Positioning and Control of Mobile Robots)

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24 pages, 73821 KiB

Open AccessArticle

An Orthogonal Wheel Odometer for Positioning in a Relative Coordinate System on a Floating Ground

by Zhiguo Lu, Guangda He, Ruchao Wang, Shixiong Wang, Yichen Zhang, Chong Liu, Ding Chen and Teng Hou

Appl. Sci. 2021, 11(23), 11340; https://doi.org/10.3390/app112311340 - 30 Nov 2021

Cited by 1 | Viewed by 1692

Abstract

This paper introduces a planar positioning sensing system based on orthogonal wheels and encoders for some surfaces that may float (such as ship decks). The positioning sensing system can obtain the desired position and angle information on any such ground that floats. In view of the current method of using the IMU gyroscope for positioning, the odometer data on these floating grounds are not consistent with the real-time data in the world coordinate system. The system takes advantage of the characteristic of the orthogonal wheel, using four vertical omnidirectional wheels and encoders to position on the floating ground. We design a new structure and obtain the position and angle information of a mobile robot by solving the encoder installed on four sets of omnidirectional wheels. Each orthogonal wheel is provided with a sliding mechanism. This is a good solution to the problem of irregular motion of the system facing the floating grounds. In the experiment, it is found that under the condition that the parameters of the four omnidirectional wheels are obtained by the encoder, the influence of the angle change of the robot in the world coordinate system caused by the flotation of the ground can be ignored, and the position and pose of the robot on the fluctuating ground can be well obtained. Regardless of straight or curved motion, the error can reach the centimeter level. In the mobile floating platform experiment, the maximum error of irregular movement process is 2.43 (±0.075) cm and the RMSE is 1.51 cm. Full article

(This article belongs to the Special Issue Trajectory Analysis, Positioning and Control of Mobile Robots)

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