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Abstract In this study, the stability of a sampled‐value control system with time‐ and state‐dependent disturbance and aperiodic sampling is investigated. To expand the application class of the sampled‐value controller, the local stability on a compact set is considered under the assumption of local Lipschitz continuity on the compact set. Because the assumption is weaker than the global Lipschitz continuity, the proposed stability analysis is applicable to a wider class of controlled systems. Global stability under the assumption of global Lipschitz continuity is also considered. The effectiveness of the derived stability condition is verified by conducting numerical simulations with some control parameters variations such as the disturbance magnitude and sample interval.

Although industrial robotic arms are equipped with external cables to supply electricity, gases or other materials, cable path design is a difficult and demanding task. Herein, an efficient optimization method is proposed for automating cable path design under the assumption that the robot motion path is known. The contribution of this study was to reduce the considerable computation time required for the optimization, which was a concern in our previous work. The previous method represented candidates for cable paths as a set of parameter vectors (PVs) that included cable length and guide configurations, and then selected the optimal PV that satisfies stress constraints and provided the shortest cable path. The proposed method extracted critical poses, i.e., several static robot poses that are prone to applying stress to the cable, from the joint angle time series of the motion path, and then performed attachment and motion tests. The cable geometry for the static critical poses was simulated in the attachment test, while the geometry for dynamic robot motion was simulated in the motion test in an ascending order of the cable length among the PV candidates. Experimental results showed that the computation time for cable path optimization could be significantly reduced.

Abstract Cheetahs use a galloping gait in their fastest speed range. It has been reported that cheetahs achieve high-speed galloping by performing two types of flight through spine movement (gathered and extended). However, the dynamic factors that enable cheetahs to incorporate two types of flight while galloping remain unclear. To elucidate this issue from a dynamical viewpoint, we developed a simple analytical model. We derived possible periodic solutions with two different flight types (like cheetah galloping), and others with only one flight type (unlike cheetah galloping). The periodic solutions provided two criteria to determine the flight type, related to the position and magnitude of ground reaction forces entering the body. The periodic solutions and criteria were verified using measured cheetah data, and provided a dynamical mechanism by which galloping with two flight types enhances speed. These findings extend current understanding of the dynamical mechanisms underlying high-speed locomotion in cheetahs.

Abstract This study discusses a cooperative control problem of a flexible beam by two planar space robots. The goal is to control the position and orientation of the flexible structure and robots, and to suppress the vibration of the flexible structure. To solve this problem, a boundary controller based on a dynamic model represented by a hybrid PDE‐ODE model is presented. In particular, a boundary controller using the Lyapunov method is derived, and it is showed that the system becomes Lyapunov stable and that the system in the neighbourhood of the desired configuration becomes asymptotically stable. As the system has an actuation redundancy, distribute control inputs among actuators considering each actuator's performance can be distributed. Finally, several numerical simulations are carried out to investigate the validity of the proposed boundary controller.

This paper proposes a method to improve the tactile sensitivity of the fingertip by placing multiple vibrators at a remote position away from the fingertip. It is known that a fingertip's tactile sensitivity improves when vibrotactile noise is applied to the fingertip or to a position away from the fingertip, such as the wrist. This is the application of stochastic resonance to the field of haptics. Preliminary experiments in this study have shown that the improvement of a fingertip's tactile sensitivity via remote vibrotactile noise depends on the propagation of the vibration on human skin. From the results of the preliminary experiments, it is expected that the larger the noise reaching the fingertip, the smaller the detectable input. Therefore, we consider that multiple vibrators at a remote position can propagate a larger noise to the fingertip and further improve the fingertip's tactile sensitivity compared to the use of only one vibrator as occurred in a previous study. Finite element analysis was performed so that the noises from multiple vibrators were properly superimposed at the fingertip. To synchronize the arrival of the noises at the fingertip from the multiple vibrators, we determined the positions of the vibrators and the time when each vibrator started generating noise. The results of a subject experiment confirmed that the proposed method significantly improved fingertip sensitivity compared to the case without SR or the case where only one vibrator was used.

In the field of unmanned aerial vehicles (UAVs), aerial manipulations are receiving considerable attention because of their potential application to tasks such as pick and place, detection, and inspection. However, short flight endurance times and concerns about the safety to surroundings during interacting heavily limit the expansion of aerial manipulations in real implementations. To overcome these challenges, this paper focuses on a system in which a quadrotor UAV is equipped with a lightweight and flexible arm. Based on the infinite-dimensional dynamics, the mathematic model of system is described by a hybrid partial differential equation-ordinary differential equation (PDE-ODE). An easily implementable controller is derived from a Lyapunov functional construction related to the energy of the system. The proposed controller ensures global Lyapunov stability for nonlinear system and local asymptotic stability for the linearized system. Further, it is shown that the proposed controller realizes stable motion of the aerial manipulator as well as vibration control of the flexible arm. Finally, numerical simulations are conducted to investigate the validity of the proposed controller.

The current methods of water quality monitoring tend to be costly, labor-intensive, and off-site. Also, they are not energetically sustainable and often require environmentally damaging power sources such as batteries. Microbial fuel cell (MFC) technology is a promising sustainable alternative to combat these issues due to its low cost, eco-friendly energy generation, and bio-sensing features. Extensive work has been done on using MFCs as bio-sensors or sources of power separately. However, little work has been done toward using MFCs for both applications at the same time. Additionally, previous studies using MFCs for water quality measurement have been mostly limited to laboratory conditions due to the biochemical complexity of the real-world. Another limitation of MFCs is how little power they can generate, requiring the MFC-based systems to have minimal power consumption. This work addresses these challenges and presents an energy-autonomous water quality sensing unit that uses a single MFC both as its sensory input and the sole source of power for computing the chemical oxygen demand (COD). In the proposed unit, geometric features of the voltage profile of the MFC (e.g., peak heights) are used as the inputs to a machine learning algorithm (support vector regression (SVR)). The electrical power generated by the MFC is used to drive a low-power microcontroller which logs the MFC voltage and runs the machine learning algorithm. Experimental evaluation showed that the device is capable of detecting the COD of natural pond water samples accurately (coefficient of determination $(R^{2})=0.94$ ). This work is the first demonstration of energy autonomy in an MFC-based sensing unit for measuring water quality and represents a step forward in the development of energy-autonomous sensors for environmental monitoring applications.

Quadrupedal mammals have fore-aft asymmetry in their body structure, which affects their walking and running dynamics. However, the effects of asymmetry, particularly in the transverse plane, remain largely unclear. In this study, we examined the effects of fore-aft asymmetry on quadrupedal trotting in the transverse plane from a dynamic viewpoint using a simple model, which consists of two rigid bodies connected by a torsional joint with a torsional spring and four spring legs. Specifically, we introduced fore-aft asymmetry into the model by changing the physical parameters between the fore and hind parts of the model based on dogs, which have a short neck, and horses, which have a long neck. We numerically searched the periodic solutions for trotting and investigated the obtained solutions and their stability. We found that three types of periodic solutions with different foot patterns appeared that depended on the asymmetry. Additionally, the asymmetry improved gait stability. Our findings improve our understanding of gait dynamics in quadrupeds with fore-aft asymmetry.

Cheetahs are the fastest land animal. Their galloping shows three characteristics: small vertical movement of their center of mass, small whole-body pitching movement, and large spine bending movement. We hypothesize that these characteristics lead to enhanced gait performance in cheetahs, including higher gait speed. In this study, we used a simple model with a spine joint and torsional spring, which emulate the body flexibility, to verify our hypothesis from a dynamic perspective. Specifically, we numerically searched periodic solutions and evaluated what extent each solution shows the three characteristics. We then evaluated the gait performance and found that the solutions with the characteristics achieve high performances. This result supports our hypothesis. Furthermore, we revealed the mechanism for the high performances through the dynamics of the spine movement. These findings extend the current understanding of the dynamic mechanisms underlying high-speed locomotion in cheetahs.

This paper presents a stability analysis of swarm robots, a group of multiple robots. In particular, we focus on robot swarms with heterogeneous abilities, in which each robot has a different sensing range and physical limitations, including maximum velocity and acceleration. In addition, each robot has a unique sensing region with a limited angle field of view. We previously proposed a decentralized navigation method for such heterogeneous swarm robots consisting of one leader and multiple followers. With the decentralized navigation method, a single leader can navigate for followers while maintaining connectivity and satisfying the physical limitations unique to each robot; i.e., each follower has a target robot and follows it without violating its physical limitations. In this paper, we focus on a stability analysis of such swarm robots. When the leader moves at a constant velocity, we mathematically prove that the shape and orientations of all robots eventually converge to the equilibrium state. For this, we must first prove that the equilibrium state exists. Then, we show the convergence of the state to its equilibrium. Finally, we carry out experiments and numerical simulations to confirm the stability analysis, i.e., the convergence of the swarm robots to the equilibrium states.

Horses use the transverse gallop in high-speed running. However, different animals use different gaits, and the gait preference of horses remains largely unclear. Horses have fore-aft asymmetry in their body structure and their center of mass (CoM) is anteriorly located far from the center of the body. Since such a CoM offset affects the running dynamics, we hypothesize that the CoM offset of horses is important in gait selection. In order to verify our hypothesis and clarify the gait selection mechanisms by horses from a dynamic viewpoint, we developed a simple model with CoM offset and investigated its effects on running. Specifically, we numerically obtained periodic solutions and classified these solutions into six types of gaits, including the transverse gallop, based on the footfall pattern. Our results show that the transverse gallop is optimal when the CoM offset is located at the position estimated in horses. Our findings provide useful insight into the gait selection mechanisms in high-speed running of horses.

Multi-legged animals show several types of ipsilateral interlimb coordination. Millipedes use a direct-wave gait, in which the swing leg movements propagate from posterior to anterior. In contrast, centipedes use a retrograde-wave gait, in which the swing leg movements propagate from anterior to posterior. Interestingly, when millipedes walk in a specific way, both direct and retrograde waves of the swing leg movements appear with the waves' source, which we call the source-wave gait. However, the gait generation mechanism is still unclear because of the complex nature of the interaction between neural control and dynamic body systems. The present study used a simple model to understand the mechanism better, primarily how local sensory feedback affects multi-legged locomotion. The model comprises a multi-legged body and its locomotion control system using biologically inspired oscillators with local sensory feedback, phase resetting. Each oscillator controls each leg independently. Our simulation produced the above three types of animal gaits. These gaits are not predesigned but emerge through the interaction between the neural control and dynamic body systems through sensory feedback (embodied sensorimotor interaction) in a decentralized manner. The analytical description of these gaits' solution and stability clarifies the embodied sensorimotor interaction's functional roles in the interlimb coordination.

Планирование пути для автономных мобильных устройств является важной задачей в робототехнике. При планировании пути принято использовать один из двух классических подходов: глобальный, когда карта полностью известна, и локальный, в котором устройство по мере движения обнаруживает препятствия с помощью различных бортовых датчиков. На основе этих двух подходов также создаются алгоритмы, сочетающие в себе сильные стороны глобального и локального планирования. В ходе предыдущих исследований нами был разработан и реализован в среде Matlab прототип многокритериального сплайн-алгоритма глобального построения маршрута. Алгоритм использует граф Вороного при вычислении первой аппроксимации маршрута для запуска итерационного метода, что позволило находить путь во всех конфигурациях карты при условии существования пути от начальной точки до целевой точки. В ходе итеративного поиска использовалась целевая функция, в которой каждому критерию присваивался его вес в целевой функции. Для реализации критериев в том числе использовался метод потенциальных полей. В данной статье представлена реализация модифицированного сплайн-алгоритма для применения его на реальных автономных мобильных робототехнических системах. Для этого проводится корректирование уравнений характеристических критериев оптимальности пути. Карта препятствий, представленная в ранней версии алгоритма в виде пересечений кругов, в реальных условиях может быть представлена в виде динамически изменяемой вероятностной карты на основе сетки занятости (OccupancyGrid), а робот уже не представляет из себя геометрическую точку. Для реализации сплайн-алгоритма и дальнейшего использования его в системах управления реальных мобильных робототехнических устройств исходный код прототипа алгоритма был перенесен из среды Matlab в модуль программного обеспечения, написанный на языке программирования С++. Тестирование быстродействия алгоритма и оптимальность многокритериальной целевой функции проводились в среде ROS/Gazebo, являющимся на сегодняшний день де-факто стандартом программирования и моделирования робототехнических устройств. Полученный в результате сплайн-алгоритм поиска пути можно интегрировать в системы управления наземных колесных и гусеничных робототехнических устройств, оборудованных лазерным дальномером, а также модифицировать предложенный алгоритм для использования шагающими наземными роботами, беспилотными летающими аппаратами и беспилотными судами. Алгоритм работает в режиме реального времени и параметры влияния критериев на целевую функцию доступны для динамических изменений во время движения мобильного робота.

A unified method for designing the motion of a snake robot negotiating complicated pipe structures is presented. Such robots moving inside pipes must deal with various “obstacles,” such as junctions, bends, diameter changes, shears, and blockages. To surmount these obstacles, we propose a method that enables the robot to adapt to multiple pipe structures in a unified way. This method also applies to motion that is necessary to pass between the inside and the outside of a pipe. We designed the target form of the snake robot using two helices connected by an arbitrary shape. This method can be applied to various obstacles by designing a part of the target form specifically for given obstacles. The robot negotiates obstacles under shift control by employing a rolling motion. Considering the slip between the robot and the pipe, the model expands the method to cover cases where two helices have different properties. We demonstrated the effectiveness of the proposed method in various experiments.

This paper presents an iterative learning control-based robust distributed algorithm on the formation issue for a group of differential-drive mobile robots. The fundamental robustness problem in practical application involving initial state shifts, disturbances, noises, and communication time-delays are considered. The distributed algorithm is proposed for each robot in directed network, which is based on the iterative learning rule with both predictive and current learning terms. It is shown that the convergence of formation tracking objective can be guaranteed under a matrix norm condition by using the two-dimensional analysis approach. Numerical simulation and experiment are both given to validate the effectiveness of the proposed algorithm.

In this work we present a soft crawler fabricated using a magneto-active elastomer. The crawler is controlled by an external magnetic field to produce two locomotion patterns: peristaltic and caterpillar crawling. Due to its structural simplicity, low mass, wirelessly controlled actuation and compliant body the design of this crawler has the potential to address the key challenges faced by existing crawling robots. Experimental data were gathered to evaluate the performance of the crawler locomotion in a pipe. The results validated the mathematical models proposed to estimate the distance traveled by the crawler. The crawler shows potential for use in exploration of confined spaces.

In this paper, we propose two control methods for driving a power-assisted cart made for walking assistance for the elderly. The optimal assistance ratio (OAR) and disturbance observer-based (DOB) methods properly adjust the motor output of the cart with high operational efficiency in response to changes in the environment. Healthy subjects walked with the cart on several road surfaces under various conditions, and the experimental results indicate the high operational efficiency of the two proposed methods. Meanwhile, their drawbacks are also discussed herein. The two methods can be used separately or combined according to the application. The OAR method is more suitable for indoor use, while the DOB method is applicable for outdoor applications. Combining these two methods could overcome the mentioned drawbacks.

Insects have various gaits with specific characteristics and can change their gaits smoothly in accordance with their speed. These gaits emerge from the embodied sensorimotor interactions that occur between the insect's neural control and body dynamic systems through sensory feedback. Sensory feedback plays a critical role in coordinated movements such as locomotion, particularly in stick insects. While many previously developed insect models can generate different insect gaits, the functional role of embodied sensorimotor interactions in the interlimb coordination of insects remains unclear because of their complexity. In this study, we propose a simple physical model that is amenable to mathematical analysis to explain the functional role of these interactions clearly. We focus on a foot contact sensory feedback called phase resetting, which regulates leg retraction timing based on touchdown information. First, we used a hexapod robot to determine whether the distributed decoupled oscillators used for legs with the sensory feedback generate insect-like gaits through embodied sensorimotor interactions. The robot generated two different gaits and one had similar characteristics to insect gaits. Next, we proposed the simple model as a minimal model that allowed us to analyze and explain the gait mechanism through the embodied sensorimotor interactions. The simple model consists of a rigid body with massless springs acting as legs, where the legs are controlled using oscillator phases with phase resetting, and the governed equations are reduced such that they can be explained using only the oscillator phases with some approximations. This simplicity leads to analytical solutions for the hexapod gaits via perturbation analysis, despite the complexity of the embodied sensorimotor interactions. This is the first study to provide an analytical model for insect gaits under these interaction conditions. Our results clarified how this specific foot contact sensory feedback contributes to generation of insect-like ipsilateral interlimb coordination during hexapod locomotion.

Walking animals produce adaptive interlimb coordination during locomotion in accordance with their situation. Interlimb coordination is generated through the dynamic interactions of the neural system, the musculoskeletal system, and the environment, although the underlying mechanisms remain unclear. Recently, investigations of the adaptation mechanisms of living beings have attracted attention, and bio-inspired control systems based on neurophysiological findings regarding sensorimotor interactions are being developed for legged robots. In this review, we introduce adaptive interlimb coordination for legged robots induced by various factors (locomotion speed, environmental situation, body properties, and task). In addition, we show characteristic properties of adaptive interlimb coordination, such as gait hysteresis and different time-scale adaptations. We also discuss the underlying mechanisms and control strategies to achieve adaptive interlimb coordination and the design principle for the control system of legged robots.

Motor primitives provide a modular organization to complex behaviours in both vertebrates and invertebrates. Inspired by this, here we generate motor primitives for a complex snake-like robot with screw-drive units, and thence chain and combine them, in order to provide a versatile, goal-directed locomotion for the robot. The behavioural primitives of the robot are generated using a reinforcement learning approach called “Policy Improvement with Path Integrals” (PI 2 ). PI 2 is numerically simple and has the ability to deal with high-dimensional systems. Here, PI 2 is used to learn the robot's motor controls by finding proper locomotion control parameters, like joint angles and screw-drive unit velocities, in a coordinated manner for different goals. Thus, it is able to generate a large repertoire of motor primitives, which are selectively stored to form a primitive library. The learning process was performed using a simulated robot and the learned parameters were successfully transferred to the real robot. By selecting different primitives and properly chaining or combining them, along with parameter interpolation and sensory feedback techniques, the robot can handle tasks like achieving a single goal or multiple goals while avoiding obstacles, and compensating for a change to its body shape.