Many of the conventional robot manipulators have a serial-link mechanism to imitate a human arm. In recent years, however, industries have been aggressive in putting parallel-link mechanisms into practical use to cope with various problems that no conventional serial-link mechanisms have ever been able to solve. Under the circumstances, this paper describes a parallel-wire driven system, one of the parallel mechanisms. It is a system to drive a controlled object with flexible and light wires instead of rigid links. It has many advantages over conventional serial-link mechanisms or other ordinary parallel-link mechanisms. This paper first overviews previous studies on parallel-wire driven robots, and then details the mechanism and control of these systems, as well as examples of their application.

Intelligent automobiles equipped with active safety methods whose objective is to reduce accidents caused by human problems such as careless driving and loss of consciousness, have got the social acceptance widely which are recognized by introducing collision avoidance brakes to the market. Active safety and automated driving technologies of intelligent automobiles were featured at Tokyo Motor Show 2015. Their displays attracted much attention.

It is necessary to propose new technologies continuously by the technical subject of active safety and automated driving, for example, relation of cooperative driving by a vehicle system and a driver, from the restrictions of originality of technical developments and the liability issues at the time of an accident.

Even so, users worldwide expect much from the dynamic future of transportation for safety and active life.

This special issue features seven papers carefully reviewed by field specialists.

I would like to express my heartfelt appreciation to the authors who have contributed their valuable research results to this special issue and to the reviewers who provided their invaluable expertise.

I would also like to thank members of the Journal of Robotics and Mechatronics board for giving me the unique opportunity to plan and coordinate this issue.

Autonomous driving has attracted attention in recent years from the viewpoint of energy consumption and traffic accident prevention; hence, its introduction has been desired. In Japan, various accident prevention safety technologies were developed for cooperative control between the driver and the vehicle system. For example, “adaptive cruise control system” and “lane departure warning system” were developed in the 1990s and “lane keeping assist system” and “braking control device for reducing collision damage” in the early stages of the 2000s. Later in Europe, autonomous driving systems were actively studied, and an automated braking system to avoid collisions was introduced in the market in the second half of the 2000s. Studies and development have been promoted for the practical use of active safety technologies based on autonomous driving technologies. Autonomous driving technologies could be applied to various cases, such as convoy travelling to compensate for the insufficient number of professional drivers or to improve their work environment, last-one-mile travelling from a public transportation station to home for the elderly, people who have children and people who need assistance, dead-man system for sudden illness of the driver, and automated parking for assisting the driver who is not good at it, or for the parking space to be effectively used. In this paper, an overview of the transition and history of vehicular technologies for safety and reliability is given. In particular, active safety technologies for traffic accident prevention and the necessary related technology trend are reviewed, and future problems are pointed out.

For realizing autonomous vehicle driving and advanced safety systems, it is necessary to achieve accurate vehicle localization in cities. This paper proposes a method of accurately estimating vehicle position by matching a map and line segment features detected from images captured by a camera. Features such as white road lines, yellow road lines, road signs, and curb stones, which could be used as clues for vehicle localization, were expressed as line segment features on a two-dimensional road plane in an integrated manner. The detected line segments were subjected to bird’s-eye view transformation to transform them to the vehicle coordinate system so that they could be used for vehicle localization regardless of the camera configuration. Moreover, an extended Kalman filter was applied after a detailed study of the line observation errors for realizing real-time estimation. Vehicle localization was tested under city driving conditions, and the vehicle position was identified with sub-meter accuracy.

Collisions in Japan between vehicles during right turns account for a high number of other intersection accidents. We present collision avoidance that introduces speed control assistance combined with autonomous emergency braking when vehicles approach and a collision becomes imminent. Our proposal uses on-board sensors such as radar and cameras to handle situations without depending on X2X communication and infrastructure. We also propose a speed control algorithm. A “vehicle-in-the-loop test” involving a virtual test drive for rapid system development verifies the effectiveness of our proposals.

This paper discusses 2-dimensional (2-D) pedestrian motion prediction and autonomous braking control for enhancing the collision avoidance performance of an active safety system. The paper targets a typical scenario involving a pedestrian walking toward a parked vehicle on a crowded urban road. The pedestrian is not expected to continue walking in a straight line. Conventional first-order motion prediction accuracy alone is not enough to predict the pedestrian motion because prediction is based on the pedestrian’s current position and velocity within a finite time. We formulated a 2-D pedestrian motion model of the parked vehicle based on learning the measured trajectory of pedestrians in the same scenario. We then designed an autonomous braking control system based on whether the vehicle will overtake a pedestrian. We evaluated the validity of the proposed autonomous braking control system in simulation experiments.

The automotive industry facilitates research and development on intelligent transport systems. One area researched intensively to enhance passenger safety is the prevention of collisions by controlling steering and braking precisely. In this study, we assume that an automatic vehicle travelling on a highway is on a collision course with an obstacle. The purpose of this research is combining steering and braking to find a set of operations the vehicle can follow to avoid the projected collision. To do this, we propose slip ratio control using sliding mode control using a real-number-coded immune algorithm (IA). CarSim (produced by Mechanical Simulation Company) provides full vehicle dynamics with 27 degrees of freedom adopted as a vehicle model. Operation waveforms are generated by linear interpolation through designated data points. The IA, which is a coded real-number expression, is used to determine data points. Our proposal’s efficiency is verified through emergency avoidance simulation using CarSim. Simulation results demonstrate operation that keeps tires from skidding using slip ratio control and halting the vehicle in the shortest braking distance possible.

This paper investigates the application of optimal micro ground vehicle (MGV) control involving overall tracking by model-predictive control (MPC) during a minimum-time maneuver. The MPC’s reference trajectory is obtained beforehand by numerically calculating an optimal control problem described as a minimum-time maneuver. Results provide nominal tracking performance and confirm the feasibility of our approach.

Intelligent passenger vehicles with autonomous capabilities will be commonplace on our roads in the near future. These vehicles will reshape the existing relationship between the driver and vehicle. Therefore, to create a new type of rewarding relationship, it is important to analyze when drivers prefer autonomous vehicles to manually-driven (conventional) vehicles. This paper documents a driving simulator-based study conducted to identify the preferences and individual driving experiences of novice and experienced drivers of autonomous and conventional vehicles under different traffic and road conditions. We first developed a simplified driving simulator that could connect to different driver-vehicle interfaces (DVI). We then created virtual environments consisting of scenarios and events that drivers encounter in real-world driving, and we implemented fully autonomous driving. We then conducted experiments to clarify how the autonomous driving experience differed for the two groups. The results showed that experienced drivers opt for conventional driving overall, mainly due to the flexibility and driving pleasure it offers, while novices tend to prefer autonomous driving due to its inherent ease and safety. A further analysis indicated that drivers preferred to use both autonomous and conventional driving methods interchangeably, depending on the road and traffic conditions.

This paper presents an experimental study on the remote control of a vehicle, focusing on driving behavior. In remote control, an operator controls a vehicle remotely using visual information captured and transmitted by a camera on the controlled vehicle without grasping sensory information related to vehicle motion, such as acceleration, vibration, or turning. The quality of visual information and a consideration of the lack of sensory information about vehicle motion are thus important for operating a vehicle safely and efficiently. This study clarifies differences in human (direct) driving and remote control driving. In step 1 of the study, we developed an experimental vehicle to evaluate the influence of visual information and evaluated the relationship between driving behavior and the quality of visual information. In step 2, we developed a remotely controlled vehicle to compare driving behavior during direct and remote driving. We also evaluated the driving behavior exhibited when there was no information on vehicle motion.

This paper describes an autonomous mobile robot stereo vision system that uses gradient feature correspondence and local image feature computation on a field programmable gate array (FPGA). Among several studies on interest point detectors and descriptors for having a mobile robot navigate are the Harris operator and scale-invariant feature transform (SIFT). Most of these require heavy computation, however, and using them may burden some computers. Our purpose here is to present an interest point detector and a descriptor suitable for FPGA implementation. Results show that a detector using gradient variance inspection performs faster than SIFT or speeded-up robust features (SURF), and is more robust against illumination changes than any other method compared in this study. A descriptor with a hierarchical gradient structure has a simpler algorithm than SIFT and SURF descriptors, and the result of stereo matching achieves better performance than SIFT or SURF.

Home service robots must possess the ability to communicate with humans, for which human detection and recognition methods are particularly important. This paper proposes methods for human detection and face recognition that are based on image processing, and are suitable for home service robots. For the human detection method, we combine the method proposed by Xia et al. based on the use of head shape with the results of region segmentation based on depth information, and use the positional relations of the detected points. We obtained a detection rate of 98.1% when the method was evaluated for various postures and facing directions. We demonstrate the robustness of the proposed method against postural changes such as stretching the arms, resting the chin on one’s hands, and drinking beverages. For the human recognition method, we combine the elastic bunch graph matching method proposed by Wiskott et al. with Face Tracking SDK to extract facial feature points, and use the 3D information in the deformation computation; we obtained a recognition rate of 93.6% during evaluation.

Robots, due to their excellent speed, accuracy and cost-effectiveness in repetitive tasks, now have a tendency to be used in rehabilitation field. A simple trajectory control of robot arm using flexible pneumatic cylinders and embedded controller which can be used as rehabilitation for human wrist is described. The system consists of the flexible robot arm, an accelerometer, an embedded microcomputer, a potentiometer and compact quasi-servo valves. The analytical model for trajectory control is proposed and applied on the flexible pneumatic robot arm. The proposed trajectory control method does not need a linearized model which is commonly used in a robot arm. The flexible structure has the characteristics of high safety such as not to cause harm to user and is suitable for use in therapeutic devices. The trajectory control can help patients recover more quickly by repeating the movements based on the patient’s individual condition. Both experiment and simulation show that the trajectory control of robot arm can be realized for several kinds of trajectory by using the proposed control method and the tested robot arm.

The number of accidental falls has been increasing among the elderly as society has aged. The main factor is a deteriorating center of balance due to declining physical performance. Another major factor is that the elderly tend to have bowlegged walking and their center of gravity position of the body tend to swing from side to side during walking. To find ways to counteract falls among the elderly, we developed walking training system to treat the gap in the center of balance. We also designed High-Performance Shoes that showed the status of a person’s balance while walking. We also produced walk assistance from the insole in which insole stiffness corresponding to human sole distribution could be changed to correct the person’s walking status. We constructed our High-Performances Shoes to detect pressure distribution during walking. Comparing normal sole distribution patterns and corrected ones, we confirmed that our assistance system helped change the user’s posture, thereby reducing falls among the elderly.

The mobility support system (MSS) that we propose expands the field of activities of personal mobility vehicles (PMVs). The system consists of a server, an ultrasonic wave (UW) system that provides self-localization in facilities, and an infrared ray (IR) system that supports passing through narrow spaces in facilities such as station ticket wickets for PMVs. Results of experiments confirmed the feasibility of the system.