New Trends in Robotics and Automation

A special issue of Machines (ISSN 2075-1702). This special issue belongs to the section "Automation and Control Systems".

Deadline for manuscript submissions: 31 July 2024 | Viewed by 18381

Special Issue Editors


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Guest Editor
School of Mechanical and Automotive Engineering, Liaocheng University, Liaocheng 252000, China
Interests: human-vehicle cooperative steering control; intelligent vehicle motion control; advanced control theory
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Guest Editor
School of Mechanical and Aerospace Engineering, Nanyang Technological University, Singapore
Interests: reinforcement learning; multi-objective optimization; robust decision and control; autonomous driving and robotics

E-Mail Website
Guest Editor
School of Mechanical and Automotive Engineering, Liaocheng University, Liaocheng 252000, China
Interests: reinforcement learning; autonomous driving

Special Issue Information

Dear Colleagues,

Robotics and automation technologies have been widely leveraged in diverse domains such as agriculture, healthcare, and transportation, and they have had significant societal impacts and benefits. As robotics and automation technologies play a central role in leading the fourth industrial revolution, new trends in robotics and automation should be thoroughly investigated to enable their development in the long run. With the rapid development of emerging technologies such as artificial intelligence (AI), digital twins (DT), Internet of Things (IoT) and human-computer interaction (HCI), there must be a booming room for robotics and automation to be discussed. Therefore, this Special Issue is proposed here to provide a forum for researchers and practitioners to exchange their latest theoretical and engineering achievements. This special issue aims to compile the latest research and development advances in robotics and automation. The topics of interest within the scope of this special issue include (although not limited to) the following:

Intelligent control in robotics;
Intelligent connected vehicles;
Trustworthy artificial intelligence;
Artificial intelligence technology applied in intelligence system;
Modeling and control of human-machine system;
System state information acquisition and parameter identification;
Application of linear and nonlinear analysis and control;
Decision-making and control with multi-source information;
Decision-making and control for multi-agent system.

Prof. Dr. Jian Wu
Dr. Xiangkun He
Dr. Guangfei Xu
Guest Editors

Manuscript Submission Information

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Keywords

  • new theories and studies in robotics
  • advanced control strategies
  • control decision-making with multi-source information
  • artificial intelligence (AI) technology applied in vehicles
  • system state information acquisition and parameter identification
  • intelligent connected vehicles
  • strategy and control of multi-agent cooperative operation
  • application of linear nonlinear analysis and control
  • modeling and control of human–machine cooperation

Published Papers (14 papers)

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Research

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35 pages, 846 KiB  
Article
Analytical Sensitivity Analysis of Dynamic Problems with Direct Differentiation of Generalized-α Time Integration
by Erich Wehrle and Veit Gufler
Machines 2024, 12(2), 128; https://doi.org/10.3390/machines12020128 - 12 Feb 2024
Viewed by 822
Abstract
In this paper, the direct differentiation of generalized-α time integration is derived, equations are introduced and results are shown. Although generalized-α time integration has found usage, the derivation and the resulting equations for the analytical sensitivity analysis via direct differentiation are [...] Read more.
In this paper, the direct differentiation of generalized-α time integration is derived, equations are introduced and results are shown. Although generalized-α time integration has found usage, the derivation and the resulting equations for the analytical sensitivity analysis via direct differentiation are missing. Thus, here, the sensitivity equations of generalized-α time integration via direct differentiation are provided. Results with generalized-α are compared with Newmark-β time integration and their sensitivities with numerical sensitivities via forward finite differencing in terms of accuracy and performance. An example is shown for each linear structural dynamics and flexible multibody dynamics. Full article
(This article belongs to the Special Issue New Trends in Robotics and Automation)
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19 pages, 4454 KiB  
Article
Collaborative Behavior for Non-Conventional Custom-Made Robotics: A Cable-Driven Parallel Robot Application
by Julio Garrido, Diego Silva-Muñiz, Enrique Riveiro, Josué Rivera-Andrade and Juan Sáez
Machines 2024, 12(2), 91; https://doi.org/10.3390/machines12020091 - 25 Jan 2024
Viewed by 1290
Abstract
The human-centric approach is a leading trend for future production processes, and collaborative robotics are key to its realization. This article addresses the challenge of designing a new custom-made non-conventional machine or robot involving toolpath control (interpolated axes) with collaborative functionalities but by [...] Read more.
The human-centric approach is a leading trend for future production processes, and collaborative robotics are key to its realization. This article addresses the challenge of designing a new custom-made non-conventional machine or robot involving toolpath control (interpolated axes) with collaborative functionalities but by using “general-purpose standard” safety and motion control technologies. This is conducted on a non-conventional cable-driven parallel robot (CDPR). Safety is assured by safe commands to individual axes, known as safe motion monitoring functionalities, which limit the axis’s speed in the event of human intrusion. At the same time, the robot’s motion controller applies an override to the toolpath speed to accommodate the robot’s path speed to the limitations of the axes. The implementation of a new Pre-Warning Zone prevents unnecessary stops due to the approach of the human operator. The article also details a real experiment that validates the effectiveness of the proposed strategy. Full article
(This article belongs to the Special Issue New Trends in Robotics and Automation)
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15 pages, 860 KiB  
Article
Synthesis of ℋ Control for Descriptor Hybrid Systems with Actuator Saturation
by Chan-eun Park
Machines 2024, 12(1), 38; https://doi.org/10.3390/machines12010038 - 05 Jan 2024
Viewed by 740
Abstract
This paper addresses a mode-dependent state-feedback H control for stochastic descriptor hybrid systems, considering both the absence and presence of actuator saturation. Firstly, the necessary and sufficient conditions for the stochastic admissibility criterion with H performance γ of the closed-loop system [...] Read more.
This paper addresses a mode-dependent state-feedback H control for stochastic descriptor hybrid systems, considering both the absence and presence of actuator saturation. Firstly, the necessary and sufficient conditions for the stochastic admissibility criterion with H performance γ of the closed-loop system are proposed. Given the proposed non-convex condition, the author reformulates it into linear matrix inequalities (LMIs). Then, to extend the result to the systems with actuator saturation, the actuator-saturated control input is expressed as a linear combination of a given state-feedback control input and a virtual control input that always remains under the saturation level. To verify this expression, the set invariant condition is also suggested by using the singular mode-dependent Lyapunov function candidate. Therefore, the conditions for the existence of both the mode-dependent state-feedback H control and the ellipsoidal shape invariant sets are successfully derived in terms of LMIs. Two numerical examples demonstrate the effectiveness of the proposed method by solving optimization problems subject to the proposed LMIs that minimize H performance γ and maximize the invariant set, respectively. Full article
(This article belongs to the Special Issue New Trends in Robotics and Automation)
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18 pages, 3958 KiB  
Article
EHB Gear-Drive Symmetric Dead-Zone Finite-Time Adaptive Control
by Shuai Wang, Qinghua Cao, Fukuo Ma and Jian Wu
Machines 2023, 11(11), 1002; https://doi.org/10.3390/machines11111002 - 30 Oct 2023
Viewed by 852
Abstract
Intelligent driving vehicles require more accurate and stable braking control. Electrohydraulic braking (EHB) systems can better adapt to the development of autonomous driving technology. The gear transmission system plays a crucial role in EHB deceleration and torque increase mechanisms. However, its dead-zone nonlinearity [...] Read more.
Intelligent driving vehicles require more accurate and stable braking control. Electrohydraulic braking (EHB) systems can better adapt to the development of autonomous driving technology. The gear transmission system plays a crucial role in EHB deceleration and torque increase mechanisms. However, its dead-zone nonlinearity poses challenges for EHB control. To address the position-control problem in the EHB gear transmission system, we propose a finite-time adaptive control method for the symmetrical dead zone. This approach combines adaptive control theory with finite-time control theory and designs parameter-updating laws for the unknown parameters in the system. Boundary estimates are introduced into the parameter-update laws and control laws to compensate for unknown disturbances. By adjusting the relevant parameters, the convergence rate can be improved, ensuring that errors converge within a specified range within a limited time. After modifying the parameter-updating laws and control laws, all closed-loop signals remain bounded. Finally, we validate the proposed control strategy through simulation and hardware-in-the-loop (HIL) testing. The results demonstrate that the control strategy developed in this study achieves high tracking accuracy and stability even in the presence of dead zones, unknown parameters, and unknown interferences in the EHB gear-drive servo system. Full article
(This article belongs to the Special Issue New Trends in Robotics and Automation)
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24 pages, 13735 KiB  
Article
Kinematic Models and the Performance Level Index of a Picking-and-Placing Hybrid Robot
by Qi Zou, Dan Zhang and Guanyu Huang
Machines 2023, 11(10), 979; https://doi.org/10.3390/machines11100979 - 23 Oct 2023
Viewed by 996
Abstract
The mobile platform of the parallel robot designed for picking and placing operations is usually equipped with one or two extra degree(s) of freedom to enable flexible grasping orientations. However, additional motors indicate extra loads for the moving platform, and the total payload [...] Read more.
The mobile platform of the parallel robot designed for picking and placing operations is usually equipped with one or two extra degree(s) of freedom to enable flexible grasping orientations. However, additional motors indicate extra loads for the moving platform, and the total payload performance shrinks. This paper proposes a spatial picking-and-placing manipulator, in which one actuator that is supposed to be installed on the mobile platform is placed far away from the mobile platform. The platform has a large workspace along one direction. The comprehensive analytical inverse and forward kinematic solutions of this robot are derived. The reachable workspace of the parallel manipulator module is then explored. The novel performance level index is designed to normalize the performance index and demonstrate the performance rank for any pose. A mathematical proof is provided for this novel index. The manipulability index is taken as an example to examine the level indicator. A multi-objective optimization is implemented to pursue optimal performance; then, the initial design and optimized results are compared in detail. A sample trajectory is provided to verify the correctness of the kinematic mathematical model of the parallel mechanism. Full article
(This article belongs to the Special Issue New Trends in Robotics and Automation)
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22 pages, 15675 KiB  
Article
Design and Implementation of a Recursive Feedforward-Based Virtual Reference Feedback Tuning (VRFT) Controller for Temperature Uniformity Control Applications
by Juan Gabriel Araque, Luis Angel, Jairo Viola and Yangquan Chen
Machines 2023, 11(10), 975; https://doi.org/10.3390/machines11100975 - 20 Oct 2023
Cited by 1 | Viewed by 1156
Abstract
Data-driven controller synthesis methods use input/output information to find the coefficients of a proposed control architecture. Virtual Reference Feedback Tuning (VRFT) is one of the most popular frameworks due to its simplicity and one-shoot synthesis style based on open-loop system response for classic [...] Read more.
Data-driven controller synthesis methods use input/output information to find the coefficients of a proposed control architecture. Virtual Reference Feedback Tuning (VRFT) is one of the most popular frameworks due to its simplicity and one-shoot synthesis style based on open-loop system response for classic regulators such as PI or PID. This paper presents a recursive VRFT framework to extend VRFT into high-order controllers with more complex structures. The framework first defines a reference model and controller structure, then uses the open-loop data to compute the virtual reference and error signals, and, finally, uses these to find the controller parameters via an optimization algorithm. Likewise, the recursive VRFT controller performance is improved by adding a model-based feedforward loop to improve reference signal tracking. The recursive method is tested to design a temperature uniformity control system. The obtained results show that the recursive VRFT with a feedforward improves the system response while allowing more complex controller synthesis. Full article
(This article belongs to the Special Issue New Trends in Robotics and Automation)
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17 pages, 3919 KiB  
Article
High-Performance Lightweight Fall Detection with an Improved YOLOv5s Algorithm
by Yuanpeng Wang, Zhaozhan Chi, Meng Liu, Guangxian Li and Songlin Ding
Machines 2023, 11(8), 818; https://doi.org/10.3390/machines11080818 - 10 Aug 2023
Viewed by 1293
Abstract
The aging population has drastically increased in the past two decades, stimulating the development of devices for healthcare and medical purposes. As one of the leading potential risks, the injuries caused by accidental falls at home are hazardous to the health (and even [...] Read more.
The aging population has drastically increased in the past two decades, stimulating the development of devices for healthcare and medical purposes. As one of the leading potential risks, the injuries caused by accidental falls at home are hazardous to the health (and even lifespan) of elderly people. In this paper, an improved YOLOv5s algorithm is proposed, aiming to improve the efficiency and accuracy of lightweight fall detection via the following modifications that elevate its accuracy and speed: first, a k-means++ clustering algorithm was applied to increase the accuracy of the anchor boxes; the backbone network was replaced with a lightweight ShuffleNetV2 network to embed simplified devices with limited computing ability; an SE attention mechanism module was added to the last layer of the backbone to improve the feature extraction capability; the GIOU loss function was replaced by a SIOU loss function to increase the accuracy of detection and the training speed. The results of testing show that the mAP of the improved algorithm was improved by 3.5%, the model size was reduced by 75%, and the time consumed for computation was reduced by 79.4% compared with the conventional YOLOv5s. The algorithm proposed in this paper has higher detection accuracy and detection speed. It is suitable for deployment in embedded devices with limited performance and with lower cost. Full article
(This article belongs to the Special Issue New Trends in Robotics and Automation)
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11 pages, 1433 KiB  
Article
Visual Place Recognition in Changing Environments with Sequence Representations on the Distance-Space Domain
by Ioannis Tsampikos Papapetros, Ioannis Kansizoglou, Loukas Bampis and Antonios Gasteratos
Machines 2023, 11(5), 558; https://doi.org/10.3390/machines11050558 - 16 May 2023
Cited by 1 | Viewed by 989
Abstract
Navigating in a perpetually changing world can provide the basis for numerous challenging autonomous robotic applications. With a view to long-term autonomy, visual place recognition (vPR) systems should be able to robustly operate under extreme appearance changes in their environment. Typically, the utilized [...] Read more.
Navigating in a perpetually changing world can provide the basis for numerous challenging autonomous robotic applications. With a view to long-term autonomy, visual place recognition (vPR) systems should be able to robustly operate under extreme appearance changes in their environment. Typically, the utilized data representations are heavily influenced by those changes, negatively affecting the vPR performance. In this article, we propose a sequence-based technique that decouples such changes from the similarity estimation procedure. This is achieved by remapping the sequential representation data into the distance-space domain, i.e., a domain in which we solely consider the distances between image instances, and subsequently normalize them. In such a way, perturbations related to different environmental conditions and embedded into the original representation vectors are avoided, therefore the scene recognition efficacy is enhanced. We evaluate our framework under multiple different instances, with results indicating a significant performance improvement over other approaches. Full article
(This article belongs to the Special Issue New Trends in Robotics and Automation)
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23 pages, 32746 KiB  
Article
Deep Reinforcement Learning-Based Torque Vectoring Control Considering Economy and Safety
by Huifan Deng, Youqun Zhao, Fen Lin and Qiuwei Wang
Machines 2023, 11(4), 459; https://doi.org/10.3390/machines11040459 - 06 Apr 2023
Cited by 1 | Viewed by 1331
Abstract
This paper presents a novel torque vectoring control (TVC) method for four in-wheel-motor independent-drive electric vehicles that considers both energy-saving and safety performance using deep reinforcement learning (RL). Firstly, the tire model is identified using the Fibonacci tree optimization algorithm, and a hierarchical [...] Read more.
This paper presents a novel torque vectoring control (TVC) method for four in-wheel-motor independent-drive electric vehicles that considers both energy-saving and safety performance using deep reinforcement learning (RL). Firstly, the tire model is identified using the Fibonacci tree optimization algorithm, and a hierarchical torque vectoring control scheme is designed based on a nonlinear seven-degree-of-freedom vehicle model. This control structure comprises an active safety control layer and a torque allocation layer based on RL. The active safety control layer provides a torque reference for the torque allocation layer to allocate torque while considering both energy-saving and safety performance. Specifically, a new heuristic random ensembled double Q-learning RL algorithm is proposed to calculate the optimal torque allocation for all driving conditions. Finally, numerical experiments are conducted under different driving conditions to validate the effectiveness of the proposed TVC method. Through comparative studies, we emphasize that the novel TVC method outperforms many existing related control results in improving vehicle safety and energy savings, as well as reducing driver workload. Full article
(This article belongs to the Special Issue New Trends in Robotics and Automation)
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27 pages, 9453 KiB  
Article
Design and Experiment of Apple Foam Net Sleeve Packaging Machine with Posture Adjustment Function
by Shisheng He, Qun Sun, Quanjin Wang, Zhiqin Liang, Ying Zhao, Xiuhao Yu and Haigang Xu
Machines 2023, 11(4), 436; https://doi.org/10.3390/machines11040436 - 29 Mar 2023
Viewed by 1924
Abstract
Background: In this study, an apple foam net packing machine is designed to improve the efficiency of apple foam net packing, reduce the intensity of manual work, and meet the market demand for diverse forms of apple packing. Methods: Based on the analysis [...] Read more.
Background: In this study, an apple foam net packing machine is designed to improve the efficiency of apple foam net packing, reduce the intensity of manual work, and meet the market demand for diverse forms of apple packing. Methods: Based on the analysis of apple shape characteristics, a secondary posture adjustment method for apples with a vertical posture adjustment mechanism and a side posture adjustment mechanism is proposed. Based on the observation of human hand-set nets and the analysis of the mechanical characteristics of nets, a dual-system net opening method combining a net slackening system and a net opening system is proposed. Results: The experiment shows that: the apple foam net sleeve packing machine can reach 99% of the apple’s posture adjustment rate, the net opening rate can reach 99%, and the packing rate can reach 98.10%. The packing speed is 10 s/pcs, and the packing efficiency is 355–365 pcs/h. The length of the fused mesh net sleeve is mainly distributed between 138 and 143 mm, which accounts for approximately 80% of the total number of samples. Conclusions: The apples packed by this machine are neatly packaged according to specifications. It can improve the efficiency of apple foam net sleeve packing and replace manual work. Full article
(This article belongs to the Special Issue New Trends in Robotics and Automation)
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15 pages, 7593 KiB  
Article
Path Tracking Control of Commercial Vehicle Considering Roll Stability Based on Fuzzy Linear Quadratic Theory
by Zhixian Fan, Yang Yan, Xiangyu Wang and Haizhu Xu
Machines 2023, 11(3), 382; https://doi.org/10.3390/machines11030382 - 13 Mar 2023
Cited by 2 | Viewed by 1108
Abstract
Commercial vehicles generally drive at a higher speed on structured expressways, and their higher center of mass leads to a lower rollover threshold and a greater rollover risk while steering. Therefore, the design of a lateral trajectory-tracking control strategy for commercial vehicles should [...] Read more.
Commercial vehicles generally drive at a higher speed on structured expressways, and their higher center of mass leads to a lower rollover threshold and a greater rollover risk while steering. Therefore, the design of a lateral trajectory-tracking control strategy for commercial vehicles should not only consider the accuracy of trajectory tracking but also consider roll stability. Based on this control objective, a fuzzy linear quadratic controller was designed in this study to ensure rolling stability in the path-tracking control process and improve the adaptability of the strategy to the driving scenario. Firstly, a steering and braking cooperative control model based on the four-degree-of-freedom model and the multi-point preview model was established. Then, a path tracking controller considering roll stability was designed based on the linear quadratic theory. On this basis, a fuzzy linear quadratic controller was designed to realize the online optimization of cost function weights. Finally, the effectiveness of the control strategy was verified using co-simulation and hardware-in-loop experiments. The results show that the designed controller can effectively adjust the weight of path-tracking and stability according to the vehicle’s state. This effectively improves the vehicle’s control distribution problem. Full article
(This article belongs to the Special Issue New Trends in Robotics and Automation)
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14 pages, 4916 KiB  
Article
An LWPR-Based Method for Intelligent Lower-Limb Prosthesis Control by Learning the Dynamic Model in Real Time
by Yi Liu, Honglei An, Hongxu Ma and Qing Wei
Machines 2023, 11(2), 186; https://doi.org/10.3390/machines11020186 - 30 Jan 2023
Viewed by 1315
Abstract
A significant number of people in the world suffer from limb losses, while prosthesis is the hopeful way to help the amputees back to normal life. Recently, the most popular control method used in intelligent prosthesis is FSM-IC (finite state machine with impedance [...] Read more.
A significant number of people in the world suffer from limb losses, while prosthesis is the hopeful way to help the amputees back to normal life. Recently, the most popular control method used in intelligent prosthesis is FSM-IC (finite state machine with impedance control), which requires a significant amount of manual parameter adjustments to achieve a good model compensation in a discrete way. Taking the lower-limb prosthesis as the research object, this paper applies an LWPR (locally weighted projection regression) model to learn the dynamic model of a prosthesis in real time in order to achieve a better model compensation in a continuous way and propose scientific experimental schemes to verify the control method. First, the basic control framework of lower-limb prosthesis is given. Then, the control law is derived on the basis of model building and LWPR’s addition. Finally, the proper experimental schemes are designed to carry out the control method effectively in a safe way. The experimental results show that the control law with the LWPR model can greatly improve the tracking performance during the swing phase and obtain rather good compliance during the stance phase. Moreover, the results also indicate that the LWPR model can approximate the dynamic model online. This method is hoped to be extended to more applications and fields. Full article
(This article belongs to the Special Issue New Trends in Robotics and Automation)
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18 pages, 6898 KiB  
Article
Narrow Tilting Vehicle Drifting Robust Control
by Dongxin Xu, Yueqiang Han, Xianghui Han, Ya Wang and Guoye Wang
Machines 2023, 11(1), 90; https://doi.org/10.3390/machines11010090 - 10 Jan 2023
Cited by 2 | Viewed by 1400
Abstract
The narrow tilting vehicle receives extensive public attention because of traffic congestion and environmental pollution, and the active rolling motion control is a traffic safety precaution that reduces the rollover risk caused by the structure size of the narrow vehicle. The drifting motion [...] Read more.
The narrow tilting vehicle receives extensive public attention because of traffic congestion and environmental pollution, and the active rolling motion control is a traffic safety precaution that reduces the rollover risk caused by the structure size of the narrow vehicle. The drifting motion control reflects the relatively updated attentive research of the regular-size vehicle, which can take full advantage of the vehicle’s dynamic performance and improve driving safety, especially when tires reach their limits. The narrow tilting vehicle drifting control is worthy of research to improve the driving safety of the narrow tilting vehicle, especially when tires reach the limit. The nonlinear narrow tilting vehicle dynamic model is established with the UniTire model to describe the vehicle motion characteristics and is simplified to reduce the computation of the drifting controller design. The narrow tilting vehicle drifting controller is designed based on the robust theory with uncertain external disturbances. The controller has a wide application, validity, and robustness and whose performance is verified by realizing different drifting motions with different initial driving motions. The narrow tilting vehicle drifting robust control has some practical and theoretical significance for more research. Full article
(This article belongs to the Special Issue New Trends in Robotics and Automation)
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Review

Jump to: Research

23 pages, 3978 KiB  
Review
A Survey on Path Planning for Autonomous Ground Vehicles in Unstructured Environments
by Nan Wang, Xiang Li, Kanghua Zhang, Jixin Wang and Dongxuan Xie
Machines 2024, 12(1), 31; https://doi.org/10.3390/machines12010031 - 02 Jan 2024
Viewed by 1451
Abstract
Autonomous driving in unstructured environments is crucial for various applications, including agriculture, military, and mining. However, research in unstructured environments significantly lags behind that in structured environments, mainly due to the challenges posed by harsh environmental conditions and the intricate interactions between vehicles [...] Read more.
Autonomous driving in unstructured environments is crucial for various applications, including agriculture, military, and mining. However, research in unstructured environments significantly lags behind that in structured environments, mainly due to the challenges posed by harsh environmental conditions and the intricate interactions between vehicles and terrains. This article first categorizes unstructured path planning into hierarchical and end-to-end approaches and then the special parts compared to structured path planning are emphatically reviewed, such as terrain traversability analysis, cost estimation, and terrain-dependent constraints. This article offers a comprehensive review of the relevant factors, vehicle–terrain interactions, and methods of terrain traversability analysis. The estimation methods of safety cost, energy cost, and comfort cost are also emphatically summarized. Moreover, the constraints caused by the limits of terrains and vehicles are discussed. The applications of algorithms in recent articles for path planners are reviewed. Finally, crucial areas requiring further research are analyzed in unstructured path planning. Full article
(This article belongs to the Special Issue New Trends in Robotics and Automation)
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