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The road mobility system is undergoing a paradigm shift towards more sustainable, efficient, safer and smarter transportation. In this context, mechatronic systems requires an ever increasing combination of mechanical, electrical/electronic, control and information disciplines. In addition, emerging smart technologies, including artificial intelligence, cybernetics, internet of things, as well as high-performance

The affiliations of Linlin Li, Jie Huang, and Sumeet S. Aphale, authors of the above-named article [ibid., vol. 26, no. 1, pp. 24–32, Feb. 2021] are corrected here.

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This article presents the dynamic modeling and trajectory tracking control of the industrial tractor–trailers vehicle composed of a full-size car-like tractor and multiple full trailers. To eliminate the high uncertainty of the kinematic and dynamic parameters of the trailers in the model, we propose to install a force sensor to monitor the forces exerted on the tractor in real time. With the force

The flexible-joint robot has superior attractive features because of its high mobility, high load ratio, high torque fidelity, robustness for external disturbance, task adaptability, and safety. In this article, an autonomous mobile manipulator driven by the designed series elastic actuators is developed. A complete dynamic model of a nonholonomic mobile manipulator including a mobile platform and

This article investigates a novel active-sensing-based obstacle avoidance paradigm for flying robots in dynamic environments. Instead of fusing multiple sensors to enlarge the field of view (FOV), we introduce an alternative approach that utilizes a stereo camera with an independent rotational degree of freedom to sense the obstacles actively. In particular, the sensing direction is planned heuristically

The humanoid robot, one of the ideal unmanned systems, has the potential to perform tasks currently carried out by human workers in industry, manufacturing, service, and disaster response. In such complicated environments with unknown disturbances, compliance is important for a humanoid robot, especially a position-controlled one, to maintain balance while performing a task. This article presents a

Effectively predicting interactive behaviors of traffic participants in the urban road is the key to successful decision-making and motion planning of intelligent vehicles. In this article, based on the data collected from vehicle on-board sensors, a graph-neural-network-based multitask learning framework (GNN-MTLF) is proposed to accurately predict trajectories of traffic participants with interactive

This study applies nonlinear model predictive control (NMPC) to the torque-vectoring (TV) and front-to-total anti-roll moment distribution control of a four-wheel-drive electric vehicle with in-wheel-motors, a brake-by-wire system, and active suspension actuators. The NMPC cost function formulation is based on energy efficiency criteria, and strives to minimize the power losses caused by the longitudinal

Cabin heating requirement and engine efficiency degradation in cold weather lead to considerable increase in fuel consumption of hybrid electric vehicles (HEVs). This article focuses on the development of a real-time control framework for integrated power and thermal management (i-PTM) of a connected HEV through incorporating vehicle speed preview informed by traffic connectivity. To evaluate the ceiling

Accurately identifying the aging-related parameters of a lithium-ion electrochemical model is crucial for the advanced battery management systems over the cells’ service life. However, the multiparametric and highly nonlinear mathematical structures of the physical model heighten the difficulty for parameterization. Thus, analyzing the influence of degraded parameters on model output holds the key

Some vehicle state information that cannot be measured by in-vehicle sensors is quite important for the active safety control of intelligent vehicles. To obtain these key information in real-time, many advanced estimation algorithms are proposed. However, the existing studies focus on the effect of sensor measurement noise on estimation accuracy and rarely consider the impact of sensor data loss. In

Road management systems are to improve in terms of integrity, mobility, sustainability, and safety by the adoption of artificial intelligence and Internet of Things services. This article introduces the concept of covert attacks on autonomous vehicles which can jeopardize the safety of passengers. Covert attacks are designed to manipulate outputs of cyber physical systems through network channels in

Advanced driver assistance systems (ADAS) aim to increase safety and reduce mental workload. However, the gap in the understanding of the closed-loop driver–vehicle interaction often leads to reduced user acceptance. In this article, an optimal torque control law is calculated online in the model predictive control (MPC) framework to guarantee continuous guidance during the steering task. The research

Mobile robots play a crucial role in cleaning, maintenance, and surveillance applications. This article advocates for the use of a novel robust output feedback based path following controller, for a class of self-reconfigurable mobile robot under actuator saturation. The reconfigurability property of such platforms is captured via an uncertain Euler–Lagrange dynamics. The proposed control framework

Precise positioning is the basic condition for intelligent vehicles to complete perception, decision making and control tasks. In response to this challenge, in this article, lidar simultaneous localization and mapping (SLAM) is taken as the research object, and a SLAM system is designed that integrates motion compensation and ground information removal functions, and can construct a real-time environment

Due to the complexity of a multimode plug-in hybrid electric vehicle (PHEV) powertrain, the energy management strategy of the said powertrain is a prime candidate for the application of optimal control methods. This article presents a predictive control strategy for optimal mode selection and powertrain control for a multimode PHEV capable of real-time control. This method utilizes predictions of future

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With the increasing requirements for vehicle mobility and transport efficiency, the amphibious fly-drive vehicle has attracted more widespread attention. This article presents a novel fly-drive vehicle driven by rotor-wing in the air and Ackerman chassis on the road. The vehicle is designed to achieve continuous air–land motion. To describe the multimodal motion, an integrated dynamic model is proposed

This article addresses the dynamic formation reconstruction and trajectory replanning problem in the air patrol task using multiple fixed-wing unmanned aerial vehicle formations. Unlike most of the formation flying related work, this article considers a more practical issue that some of the vehicles may break down during operation. In this case, a more reasonable coping strategy is proposed which is

This article proposes a human-knowledge-integrated particle swarm optimization (Hi-PSO) scheme to globally optimize the design of the hydraulic-electromagnetic energy-harvesting shock absorber (HESA) for road vehicles. A newly developed k-fold swarm learning framework is the key to the Hi-PSO scheme, which runs k groups (folds) of individual local optimization (using a selected learning cycle), and

In this article, cooperative circumnavigation (CCN) is studied for groups of networked unmanned aerial vehicles (UAVs) under a directed interaction topology. The CCN drives UAVs to given planar ellipses with desired spatial formation. A first contribution is that based on affine transformations, CCN control design is structured, which can deploy UAVs on spatial orbits with different radii concerning

To improve electric vehicle (EV) mileage, motors must be designed for higher power density and efficiency. Winding technology with a high fill factor decreases the motor volume by reducing the unnecessary area of the slot. A motor conductor with a large cross-sectional area generates additional losses due to ac resistance, reducing the efficiency of the motor. Traction motors designed under these conditions

In this article, a novel approach of decision-making and motion control is designed for realizing safe and personalized driving of autonomous vehicles. A new lane-change intention generation model and a new lane-change decision-making algorithm are proposed. The feature of the proposed decision-making module is that the interactions between the ego vehicle and other surrounding vehicles are represented

In this article, a robust nonlinear model predictive control (NMPC) scheme is proposed for the visual servoing of quadrotors subject to external disturbances. By using the virtual camera approach, the image moments are defined in the virtual camera plane and adopted as visual features to derive the decoupled image kinematics. As a result, the image-based visual servoing (IBVS) system model is established

This article addresses the fault-tolerant control problem of two-wheel-drive (2WD) mobile robots under actuator faults. To improve the actuation redundancy, a physical link is employed to connect two 2WD mobile robots. The kinematics and dynamics of such a two-robot system are modeled. An adaptive fault-tolerant control scheme is developed to make the two-robot system asymptotic track a desired reference

An event-triggered-based (ETB) discrete-time neural control is studied for a quadrotor unmanned aerial vehicle (UAV) with external disturbances and input saturation by using the discrete-time disturbance observer (DTDO). First, the ETB mechanism of the neural network is given and the Sigmoid-type function is employed to tackle the problem of input saturation. Then, the DTDO is designed and the saturation

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In this article, we address the simultaneous estimation problem of the lateral speed, the steering input, and the effective engine torque, which play a fundamental role in vehicle handling, stability control, and fault diagnosis of autonomous ground vehicles. Due to the involved longitudinal-lateral coupling dynamics and the presence of unknown inputs (UIs), a new nonlinear observer design technique

Traffic accidents occurred frequently on roads, which bring huge losses to society. The purpose of this article is to extract the important influence factors of traffic accidents, reduce the probability of road traffic accidents, and support the basis for the decision-making of unmanned vehicles. For all this, an improved artificial neural network method is proposed to predict and analyze the severity

This article focuses on the position control problem for permanent magnet dc torque motor systems. An adaptive position tracking controller is proposed with online parameter adaptation. The position of the permanent magnet dc torque motor under the proposed strategy tracks the reference signal with fixed-time convergence. Different from previous fixed-time control methods, the approach proposed in

This article designed a soft bending actuator (SBA) and presented a neural-network-based tracking control strategy for such an actuator. To achieve high-precision control, a visual feedback system was established by using a high-speed camera to dynamically compute the corresponding central angle which described the curvature of the SBA. Considering its nonlinear features, the echo state Gaussian process

A magnetic drug-targeting system featuring real-time imaging, guidance, and local heating is required for more precise drug targeting and minimization of side effects. In this article, we present a novel electromagnetic navigation and heating system that not only guides and navigates magnetic nanoparticles (MNPs) with real-time imaging feedback, but also uses focused MNP heating to release drugs while

State of health (SOH) is essential for battery management, timely maintenance, and safety incident avoidance. For specific applications, a variety of SOH estimation methods have been proposed. However, it is often difficult to apply these methods to other applications. In this article, a novel feature extraction method is proposed to extract health indicators (HIs) from general discharging conditions

This article features a novel sliding mode controller for robotic arms using nonlinear model-based switching functions. The new controller is experimentally validated on a 7-DOF exoskeleton arm used for upper-limb rehabilitation applications. The proposed approach features a novel concept using model-based switching functions in the sliding mode controller, which leads to considerable simplifications

This article discusses nonprehensile manipulation of an asymmetric object using a robotic manipulator from a motion planning point of view. Four different aspects of the problem will be analyzed:object stability, motion planning, manipulator control, and experimental validation. Specifically, via an analysis of marginal stability of an object resting on a moving tray, the work establishes the critical

Scanner-based robotic grinding has shown great potential for replacing the manual method to achieve efficient and automatic manufacturing. However, its application has been limited by the grinding quality, which is affected by the pose errors between the robot and other workcells (a scanner, a workpiece, and a tool). To improve the pose accuracy, this article proposes a novel estimation method for

Full state feedback (FSF) controllers for series elastic actuators bridge the gap between impedance and admittance controllers. For humanoid robots—which must stably accomplish both stiff and soft behaviors—FSF controllers are ideal candidate joint controllers. However, previous work on FSF gain tuning has used a nonlinear passivity analysis which does not account for time delay and can result in unstable

This article explores a technique to leverage curved surfaces for producing preferential buckling that can be used to create forward thrust in flapping-wing devices. We present a novel concept for using anisotropically buckling beams in robot locomotion, facilitated via an analytical and finite-element-based analyses. We demonstrate that with symmetric flapping inputs from a motor, buckling beams can

In this article, we deal with rehabilitation robot robust control in order to obtain best performance in the human-robot interaction. This class of system is subject to abrupt changes due to exogenous inputs and parameter variations caused, mainly, by the human dynamic behavior. In this context, Markovian jump linear systems offer suitable tools to model and control of this class of interactions. We

In recent years, many unmanned vehicle designs and autonomous driving functions have been introduced in the automotive industry to increase the safety and versatility of multiple vehicle designs. It is critical to select a plant vehicle model and a compact uncertainty representation regardless of the vehicle scale for vast deployment. This article introduces a dimensionless representation of a dynamic

Surface topography plays a key role in the service performance of parts, and is often used as a metric for detecting machining states as well. Hence, it is of great importance to online predict the surface topography to avoid surface deterioration and machining faults. However, alternative solutions for this purpose remain to be developed. This article presents a generative adversarial network to predict

Presents the table of contents for this issue of this publication.

Provides a listing of current staff, committee members and society officers.

Over the past few decades, intelligentization, supported by artificial intelligence (AI) technologies, has become an important trend for industrial manufacturing, accelerating the development of smart manufacturing. In modern industries, standard AI has been endowed with additional attributes, yielding the so-called industrial artificial intelligence (IAI) that has become the technical core of smart

Prospective authors are requested to submit new, unpublished manuscripts for inclusion in the upcoming event described in this call for papers.

Advertisement: TechRxiv is a free preprint server for unpublished research in electrical engineering, computer science, and related technology. Powered by IEEE, TechRxiv provides researchers across a broad range of fields the opportunity to share early results of their work ahead of formal peer review and publication. Researchers are asked to upload their unpublished research.

Provides instructions and guidelines to prospective authors who wish to submit manuscripts.

Untethered annelids-inspired soft robots can be used in space-confined compliant interactions where remote actuation is necessary. In contrast to their fully-soft counterparts, incorporating origami concepts can streamline modeling and control while maintaining compliance. However, more comprehensive untethered locomotions from a single deployable robot remain research challenges, and there are only

A novel efficiency optimization strategy combined with a position estimation method is proposed for switched reluctance generators (SRGs) in this article. This practical performance improvement strategy can expand the application of SRGs small-scale wind energy generation system, which is a good solution for mitigating the fossil energy crisis. First, the position estimation method based on current

Due to the complex transfer paths of vibration signals, and a large number of vibration excitations, fault diagnosis of reciprocating compressors (RCs) has become one of the most challenging problems in the field of health monitoring. Focusing on fault diagnosis, a novel method, which will be referred to in this paper as mode isolation convolutional deep belief network (MI-CDBN), is proposed from the