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Autonomous Mobile Robots: Real-Time Sensing, Navigation, and Control

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A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Electronic Sensors".

Deadline for manuscript submissions: closed (15 October 2021) | Viewed by 111937

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Special Issue Editor

Dr. Carlos J. Pérez Del Pulgar

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Guest Editor

Department of Systems Engineering and Automation, Universidad de Málaga, Andalucía Tech, 29071 Malaga, Spain
Interests: space robotics; machine learning; path and motion planning; control systems for space
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Autonomous mobile robots are getting more and more attention since they can be used for different applications such as precision agriculture, field robotics, search and rescue, planetary exploration, etc. The use of sensors, together with navigation and control algorithms, allows improving autonomy in different manners. On the one hand, the use of exteroceptive sensors as LIDARs, stereocameras, ultrasonic devices, IR cameras, and others helps mobile robots to get rich information about the surrounding environment, useful to support robot navigation in combination with path and motion planning algorithms. On the other hand, proprioceptive sensors, such as current sensors, IMUs, vibration sensors, wheel sinkage sensors, become useful in improving robot awareness of the surface it is traversing. A combination of both kinds of sensors, together with artificial intelligence algorithms, would improve the autonomous navigation and control of robots in the aforementioned applications.

Therefore, this Special Issue includes but is not limited to the following topics:

Novel perception systems for robot navigation and localization;
Novel sensors for robot localization;
Robot localization without GNSS;
Novel proprioceptive sensors onboard mobile robots;
Path planning for mobile robots;
Motion planning for mobile manipulators;
Field tests with autonomous mobile robots;
Applications of mobile robots.

Dr. Carlos J. Pérez Del Pulgar
Guest Editor

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Keywords

mobile robots
rovers
exteroceptive sensors
proprioceptive sensors
path planning
motion planning
field tests

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Published Papers (11 papers)

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Research

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17 pages, 35565 KiB

Open AccessArticle

Lane Departure Assessment via Enhanced Single Lane-Marking

by Yiwei Luo, Ping Li, Gang Shi, Zuowei Liang, Lei Chen and Fengwei An

Sensors 2022, 22(5), 2024; https://doi.org/10.3390/s22052024 - 4 Mar 2022

Cited by 2 | Viewed by 2529

Abstract

Vision-based Lane departure warning system (LDWS) has been widely used in modern vehicles to improve drivability and safety. In this paper, a novel LDWS with precise positioning is proposed. Calibration strategy is first presented through a 3D camera imaging model with only three parallel and equally spaced lines, where the three angles of rotation for the transformation from the camera coordinate system to the world coordinate system are deduced. Then camera height is calculated compared to the previous works using a measured one with potential errors. A criterion for lane departure warning with only one of the two lane-markings is proposed to estimate both yaw angle and distance between the lane-markings and the vehicle. Experiments show that calibration strategy can be easily set up and achieve an average of 98.95% accuracy on the lane departure assessment. Full article

(This article belongs to the Special Issue Autonomous Mobile Robots: Real-Time Sensing, Navigation, and Control)

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19 pages, 3506 KiB

Open AccessArticle

Modified Artificial Potential Field for the Path Planning of Aircraft Swarms in Three-Dimensional Environments

by Rafael Monteiro Jorge Alves Souza, Gabriela Vieira Lima, Aniel Silva Morais, Luís Cláudio Oliveira-Lopes, Daniel Costa Ramos and Fernando Lessa Tofoli

Sensors 2022, 22(4), 1558; https://doi.org/10.3390/s22041558 - 17 Feb 2022

Cited by 22 | Viewed by 4638

Abstract

Path planning techniques are of major importance for the motion of autonomous systems. In addition, the chosen path, safety, and computational burden are essential for ensuring the successful application of such strategies in the presence of obstacles. In this context, this work introduces a modified potential field method that is capable of providing obstacle avoidance, as well as eliminating local minima problems and oscillations in the influence threshold of repulsive fields. A three-dimensional (3D) vortex field is introduced for this purpose so that each robot can choose the best direction of the vortex field rotation automatically and independently according to its position with respect to each object in the workspace. A scenario that addresses swarm flight with sequential cooperation and the pursuit of moving targets in dynamic environments is proposed. Experimental results are presented and thoroughly discussed using a Crazyflie 2.0 aircraft associated with the loco positioning system for state estimation. It is effectively demonstrated that the proposed algorithm can generate feasible paths while taking into account the aforementioned problems in real-time applications. Full article

(This article belongs to the Special Issue Autonomous Mobile Robots: Real-Time Sensing, Navigation, and Control)

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41 pages, 1087 KiB

Open AccessArticle

Design of Secure Microcontroller-Based Systems: Application to Mobile Robots for Perimeter Monitoring

by Dmitry Levshun, Andrey Chechulin and Igor Kotenko

Sensors 2021, 21(24), 8451; https://doi.org/10.3390/s21248451 - 17 Dec 2021

Cited by 3 | Viewed by 4659

Abstract

This paper describes an original methodology for the design of microcontroller-based physical security systems and its application for the system of mobile robots. The novelty of the proposed methodology lies in combining various design algorithms on the basis of abstract and detailed system representations. The suggested design approach, which is based on the methodology, is modular and extensible, takes into account the security of the physical layer of the system, works with the abstract system representation and is looking for a trade-off between the security of the final solution and the resources expended on it. Moreover, unlike existing solutions, the methodology has a strong focus on security. It is aimed at ensuring the protection of the system against attacks at the design stage, considers security components as an integral part of the system and checks if the system can be designed in accordance with given requirements and limitations. An experimental evaluation of the methodology was conducted with help of its software implementation that consists of Python script, PostgreSQL database, Tkinter interface and available for download on our GitHub. As a use case, the system of mobile robots for perimeter monitoring was chosen. During the experimental evaluation, the design time was measured depending on the parameters of the attacker against which system security must be ensured. Moreover, the software implementation of the methodology was analyzed in compliance with requirements and compared with analogues. The advantages and disadvantages of the methodology as well as future work directions are indicated. Full article

(This article belongs to the Special Issue Autonomous Mobile Robots: Real-Time Sensing, Navigation, and Control)

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12 pages, 2726 KiB

Open AccessCommunication

An Improved Timed Elastic Band (TEB) Algorithm of Autonomous Ground Vehicle (AGV) in Complex Environment

by Jiafeng Wu, Xianghua Ma, Tongrui Peng and Haojie Wang

Sensors 2021, 21(24), 8312; https://doi.org/10.3390/s21248312 - 12 Dec 2021

Cited by 35 | Viewed by 8861

Abstract

In recent decades, the Timed Elastic Band (TEB) algorithm is widely used for the AGV local path panning because of its convenient and efficiency. However, it may make a local detour when encountering a curve turn and cause excessive energy consumption. To solve this problem, this paper proposed an improved TEB algorithm to make the AGV walk along the wall when turning, which shortens the planning time and saves energy. Experiments were implemented in the Rviz visualization tool platform of the robot operating system (ROS). Simulated experiment results reflect that an amount of 5% reduction in the planning time has been achieved and the velocity curve implies that the operation was relatively smooth. Practical experiment results demonstrate the effectiveness and feasibility of the proposed method that the robots can avoid obstacles smoothly in the unknown static and dynamic obstacle environment. Full article

(This article belongs to the Special Issue Autonomous Mobile Robots: Real-Time Sensing, Navigation, and Control)

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29 pages, 23633 KiB

Open AccessArticle

Formation Tracking Control and Obstacle Avoidance of Unicycle-Type Robots Guaranteeing Continuous Velocities

by Jose Bernardo Martinez, Hector M. Becerra and David Gomez-Gutierrez

Sensors 2021, 21(13), 4374; https://doi.org/10.3390/s21134374 - 26 Jun 2021

Cited by 11 | Viewed by 3385

Abstract

In this paper, we addressed the problem of controlling the position of a group of unicycle-type robots to follow in formation a time-varying reference avoiding obstacles when needed. We propose a kinematic control scheme that, unlike existing methods, is able to simultaneously solve the both tasks involved in the problem, effectively combining control laws devoted to achieve formation tracking and obstacle avoidance. The main contributions of the paper are twofold: first, the advantages of the proposed approach are not all integrated in existing schemes, ours is fully distributed since the formulation is based on consensus including the leader as part of the formation, scalable for a large number of robots, generic to define a desired formation, and it does not require a global coordinate system or a map of the environment. Second, to the authors’ knowledge, it is the first time that a distributed formation tracking control is combined with obstacle avoidance to solve both tasks simultaneously using a hierarchical scheme, thus guaranteeing continuous robots velocities in spite of activation/deactivation of the obstacle avoidance task, and stability is proven even in the transition of tasks. The effectiveness of the approach is shown through simulations and experiments with real robots. Full article

(This article belongs to the Special Issue Autonomous Mobile Robots: Real-Time Sensing, Navigation, and Control)

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17 pages, 5264 KiB

Open AccessArticle

Biped Walking Based on Stiffness Optimization and Hierarchical Quadratic Programming

by Xuanyang Shi, Junyao Gao, Yizhou Lu, Dingkui Tian and Yi Liu

Sensors 2021, 21(5), 1696; https://doi.org/10.3390/s21051696 - 2 Mar 2021

Cited by 11 | Viewed by 3085

Abstract

The spring-loaded inverted pendulum model is similar to human walking in terms of the center of mass (CoM) trajectory and the ground reaction force. It is thus widely used in humanoid robot motion planning. A method that uses a velocity feedback controller to adjust the landing point of a robot leg is inaccurate in the presence of disturbances and a nonlinear optimization method with multiple variables is complicated and thus unsuitable for real-time control. In this paper, to achieve real-time optimization, a CoM-velocity feedback controller is used to calculate the virtual landing point. We construct a touchdown return map based on a virtual landing point and use nonlinear least squares to optimize spring stiffness. For robot whole-body control, hierarchical quadratic programming optimization is used to achieve strict task priority. The dynamic equation is given the highest priority and inverse dynamics are directly used to solve it, reducing the number of optimizations. Simulation and experimental results show that a force-controlled biped robot with the proposed method can stably walk on unknown uneven ground with a maximum obstacle height of 5 cm. The robot can recover from a 5 Nm disturbance during walking without falling. Full article

(This article belongs to the Special Issue Autonomous Mobile Robots: Real-Time Sensing, Navigation, and Control)

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20 pages, 2075 KiB

Open AccessArticle

A Compressed Sensing Approach for Multiple Obstacle Localisation Using Sonar Sensors in Air

by Eduardo Tondin Ferreira Dias, Hugo Vieira Neto and Fábio Kurt Schneider

Sensors 2020, 20(19), 5511; https://doi.org/10.3390/s20195511 - 26 Sep 2020

Cited by 3 | Viewed by 2648

Abstract

Methods for autonomous navigation systems using sonars in air traditionally use the time-of-flight technique for obstacle detection and environment mapping. However, this technique suffers from constructive and destructive interference of ultrasonic reflections from multiple obstacles in the environment, requiring several acquisitions for proper mapping. This paper presents a novel approach for obstacle detection and localisation using inverse problems and compressed sensing concepts. Experiments were conducted with multiple obstacles present in a controlled environment using a hardware platform with four transducers, which was specially designed for sending, receiving and acquiring raw ultrasonic signals. A comparison between the performance of compressed sensing using Orthogonal Matching Pursuit and two traditional image reconstruction methods was conducted. The reconstructed 2D images representing the cross-section of the sensed environment were quantitatively assessed, showing promising results for robotic mapping tasks using compressed sensing. Full article

(This article belongs to the Special Issue Autonomous Mobile Robots: Real-Time Sensing, Navigation, and Control)

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29 pages, 27359 KiB

Open AccessArticle

Representations and Benchmarking of Modern Visual SLAM Systems

by Yuchen Cao, Lan Hu and Laurent Kneip

Sensors 2020, 20(9), 2572; https://doi.org/10.3390/s20092572 - 30 Apr 2020

Cited by 2 | Viewed by 4994

Abstract

Simultaneous Localisation And Mapping (SLAM) has long been recognised as a core problem to be solved within countless emerging mobile applications that require intelligent interaction or navigation in an environment. Classical solutions to the problem primarily aim at localisation and reconstruction of a geometric 3D model of the scene. More recently, the community increasingly investigates the development of Spatial Artificial Intelligence (Spatial AI), an evolutionary paradigm pursuing a simultaneous recovery of object-level composition and semantic annotations of the recovered 3D model. Several interesting approaches have already been presented, producing object-level maps with both geometric and semantic properties rather than just accurate and robust localisation performance. As such, they require much broader ground truth information for validation purposes. We discuss the structure of the representations and optimisation problems involved in Spatial AI, and propose new synthetic datasets that, for the first time, include accurate ground truth information about the scene composition as well as individual object shapes and poses. We furthermore propose evaluation metrics for all aspects of such joint geometric-semantic representations and apply them to a new semantic SLAM framework. It is our hope that the introduction of these datasets and proper evaluation metrics will be instrumental in the evaluation of current and future Spatial AI systems and as such contribute substantially to the overall research progress on this important topic. Full article

(This article belongs to the Special Issue Autonomous Mobile Robots: Real-Time Sensing, Navigation, and Control)

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Review

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29 pages, 6052 KiB

Open AccessReview

Path Planning for Autonomous Mobile Robots: A Review

by José Ricardo Sánchez-Ibáñez, Carlos J. Pérez-del-Pulgar and Alfonso García-Cerezo

Sensors 2021, 21(23), 7898; https://doi.org/10.3390/s21237898 - 26 Nov 2021

Cited by 179 | Viewed by 43772

Abstract

Providing mobile robots with autonomous capabilities is advantageous. It allows one to dispense with the intervention of human operators, which may prove beneficial in economic and safety terms. Autonomy requires, in most cases, the use of path planners that enable the robot to deliberate about how to move from its location at one moment to another. Looking for the most appropriate path planning algorithm according to the requirements imposed by users can be challenging, given the overwhelming number of approaches that exist in the literature. Moreover, the past review works analyzed here cover only some of these approaches, missing important ones. For this reason, our paper aims to serve as a starting point for a clear and comprehensive overview of the research to date. It introduces a global classification of path planning algorithms, with a focus on those approaches used along with autonomous ground vehicles, but is also extendable to other robots moving on surfaces, such as autonomous boats. Moreover, the models used to represent the environment, together with the robot mobility and dynamics, are also addressed from the perspective of path planning. Each of the path planning categories presented in the classification is disclosed and analyzed, and a discussion about their applicability is added at the end. Full article

(This article belongs to the Special Issue Autonomous Mobile Robots: Real-Time Sensing, Navigation, and Control)

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20 pages, 741 KiB

Open AccessEditor’s ChoiceReview

A Review of Visual-LiDAR Fusion based Simultaneous Localization and Mapping

by César Debeunne and Damien Vivet

Sensors 2020, 20(7), 2068; https://doi.org/10.3390/s20072068 - 7 Apr 2020

Cited by 271 | Viewed by 26291

Abstract

Autonomous navigation requires both a precise and robust mapping and localization solution. In this context, Simultaneous Localization and Mapping (SLAM) is a very well-suited solution. SLAM is used for many applications including mobile robotics, self-driving cars, unmanned aerial vehicles, or autonomous underwater vehicles. In these domains, both visual and visual-IMU SLAM are well studied, and improvements are regularly proposed in the literature. However, LiDAR-SLAM techniques seem to be relatively the same as ten or twenty years ago. Moreover, few research works focus on vision-LiDAR approaches, whereas such a fusion would have many advantages. Indeed, hybridized solutions offer improvements in the performance of SLAM, especially with respect to aggressive motion, lack of light, or lack of visual features. This study provides a comprehensive survey on visual-LiDAR SLAM. After a summary of the basic idea of SLAM and its implementation, we give a complete review of the state-of-the-art of SLAM research, focusing on solutions using vision, LiDAR, and a sensor fusion of both modalities. Full article

(This article belongs to the Special Issue Autonomous Mobile Robots: Real-Time Sensing, Navigation, and Control)

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Other

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18 pages, 31637 KiB

Open AccessLetter

Reactive Navigation on Natural Environments by Continuous Classification of Ground Traversability

by Jorge L. Martínez, Jesús Morales, Manuel Sánchez, Mariano Morán, Antonio J. Reina and J. Jesús Fernández-Lozano

Sensors 2020, 20(22), 6423; https://doi.org/10.3390/s20226423 - 10 Nov 2020

Cited by 15 | Viewed by 3322

Abstract

Reactivity is a key component for autonomous vehicles navigating on natural terrains in order to safely avoid unknown obstacles. To this end, it is necessary to continuously assess traversability by processing on-board sensor data. This paper describes the case study of mobile robot Andabata that classifies traversable points from 3D laser scans acquired in motion of its vicinity to build 2D local traversability maps. Realistic robotic simulations with Gazebo were employed to appropriately adjust reactive behaviors. As a result, successful navigation tests with Andabata using the robot operating system (ROS) were performed on natural environments at low speeds. Full article

(This article belongs to the Special Issue Autonomous Mobile Robots: Real-Time Sensing, Navigation, and Control)

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