This paper presents a Variable Morphing Multi-Body AUVs (VMMAUVs) concept, designed for underwater structure maintenance. This robot is capable of dynamically adjusting their structure to adapt to varying operational scenarios. The study explores two key stability mechanisms: buoyancy adjustment and aperture angle control, both aimed at optimizing the metacentric height. Through simulations and experiments with different buoyancy configurations and aperture angles, the results show that the proposed methods significantly enhance the system ’ s stability, enabling faster convergence and better posture retention. The feasibility of the control strategies is validated through various numerical simulations, demonstrating the effectiveness of angle tracking control and buoyancy adjustment in maintaining stability under dynamic oceanic conditions.

This study introduces a novel burrowing robot that achieves effective locomotion inside granular media through the synergistic integration of high-frequency vibration-induced environmental-phase-transition (EPT) and adaptive morphing. The robotic system employs three key innovations: 1) an asymmetric arm trajectory mechanism generating directional propulsion, 2) a vibration-mediated granular fluidization system reducing environmental resistance, and 3) passively adaptive claws demonstrating phase-dependent configuration changes. Experimental results demonstrate that the synchronization of morphologically adaptive claws and high-frequency vibration significantly improves locomotion performance. Additionally, numerical simulations based on Adams-EDEM coupling provide deeper insights into the interaction mechanisms between the robot and granular media. This work advances fundamental understanding of terradynamic locomotion by demonstrating environmental modification as a viable strategy for resistance reduction, while providing a bio-inspired framework for developing versatile robotic systems capable of navigating complex particulate environments.

Rescue robots require versatility and the capability to operate in various environments to carry out a diverse set of tasks effectively. The eccentric paddle (ePaddle) mechanism stands out for its high efficiency and adaptability. Generally, it is designed as a quadruped robot with a combined structure for fully-actuated control, this approach is often both inefficient and inflexible due to the requirement for repeated front-to-back paths. Unlike the fully-actuated controller that assume torso is fixed, this study proposes an under-actuated controller, consisting of a single ePaddle mechanism and a free torso for more efficient and flexible movement. Inspired by human gait, precision walking, and non-precision walking are introduced to discuss the stability of zero dynamics. Additionally, the stability condition is presented and demonstrated by numerical simulation. Since this control is based on robot dynamics, it has a high fault-tolerance and benefited from its dynamics attractor. The concept of under-actuated controller we proposed in this study is not only applicable to the ePaddle mechanism, but also to other under-actuated legged locomotion models.

This paper mathematically conceives a novel walking support device that leverages passive dynamics and coupling effects. In this model, a passive human walker is flexibly connected to an active humanoid, where the coupling effect induces a stable walking gait of the human. To understand the key mechanism of such indirect gait regulation, different actuation modes are designed for the humanoid and compared via phase-plane analysis of the steady-state gaits. Moreover, stability analysis is conducted via Poincaré map. The results show that it is difficult to enhance the human walker's stability when coupled to a humanoid robot using additional sensory information, compared to using a humanoid robot actuated with a predetermined force that employs no state feedback. The present mathematical model and our theoretical findings contribute to analysis and control design for locomotion systems with robot-human or inter-robots cooperation.

Enlightened by the creeping gait of natural snakes, snake-like robots swing joints side to side at similar tracks for generating propelling forces. However, it is not always essential to control all joints of a snake-like robot to realize the creeping gait. Therefore, in this paper, a creeping snake-like robot with partially actuated joints has been investigated, towards reducing the redundancy caused by full actuation. Essentially, this approach is composed of the following two concepts: 1) joint equipped with torsion spring mechanism bridges the passive joint to generate rhythm oscillation, and 2) harmonic joint trajectories assist the robot in generating more efficient locomotion. We hereafter demonstrated that the actuated joint dominates passive dynamics of the system, which contributes to overall motion. Meanwhile, different spring stiffness affects the motion performance. Additionally, the interaction between robot and environment through Coulomb friction has been considered to reveal the contributing factors that assist the snake-like robot to yield better locomotion performance.

The goal of this paper is to develop an ultrasonic detection device that can be mounted on an underwater snake vehicle (USV) for underwater district heating pipe (DHP) detection in the future. Ultrasonic detection technology (UDT) is the detection means used, and the cavitation defects in polyurethane (PUR) layer of DHPs are the object being detected. Due to the large thickness of PUR layer and the complex interface information of multi-layer structure, detecting defects of DHPs quantitatively is a difficult task. To address this issue, this paper proposes an approach that combines feature extraction and crow search algorithm (CSA) optimized support vector machine (SVM). Firstly, the main parameters and detection method of UDT are designed after investigation. Secondly, defective signals are pre-processed by signal processing to extract the features form three domains. Finally, four different classifiers are used to identify cavitation defects based on the feature-set. When compared among optimized random forest (RF), k-nearest neighbor (KNN), and ordinary SVM, the experimental results show that CSA-SVM had the highest accuracy in defect size prediction, and the validation-experiment verifies the practicability and feasibility of the CSA-SVM classifier. All experiments illustrate that the issue could be well solved by our method.

Undulation is the most common gait generated by legless creatures, which enables their robust and efficient locomotion in various environments. Such advantages inspired the control design of many kinds of locomotion robots. Despite their technical details, most of them realize the undulation gait via tracking predetermined trajectories called serpenoid curves, which are a group of sinusoidal waveforms with specified phase differences. This technique, however, sounds quite redundant in terms of sensing and control. Here, we investigate the research question: whether the sinusoidal waveform is necessary to be encoded in the control signal to make the whole body an “S-shape”? We use a 4-link rigid body dynamics model as a simple example, by which numerical simulations are conducted. Together with theoretical analysis, we show that undulation gait emerges naturally based on embodied position controller and filter, where binary actuation torques are required only. Our results not only discover locomotion mechanisms for significantly reducing the sensing and control requirement of generating artificial undulation gait, but also provide additional understandings for biological systems from the mechanical engineering point of view.

Biological observations on tetrapods locomotion deduce that anti-phase synchronization (APS) between fore and rear parts is beneficial for achieving a high-speed walking. On the other hand, theoretical analysis and experimental studies on quadruped robots suggest that a flexible spine potentially improves the gait efficiency and adaptability via smoothing the ground collisions. However, these two mechanisms have never been placed together by a comprehensive investigation in terms of their synergetic effect. Namely, an advanced principle is still lacking in combining the APS and the spine flexibility for quadruped walking robots. To address this issue, we construct a mathematical model for a quadruped dynamic walker under different spine conditions. First, the APS effect is generated via entrainment-based control method under a rigid spine condition. Then, flexible spines realized by three kinds of springs are compared with the rigid one via theoretical analysis. The results suggest that the APS mechanism and the flexible spine can be synergized via an appropriate deformation control. The theoretical findings not only uncover locomotion control mechanisms for quadruped walking robots, but also provide additional understandings of tetrapods dynamic walking from a mechanical engineering point of view.

This paper introduces a planar tensegrity robot that walks passively and cyclically on a gentle downhill, where its gait versatility can be strengthened by applying actuation forces on the connection cables. The novelty of this work is that we design the structure of this passive robot inspired by the rimless wheel, which naturally generates cyclic locomotion. Consequently, its mathematical model is analytically derived based on passive dynamic walking. Besides, the limb support conditions and dynamics effects induced by the collisions can be precisely determined accordingly. Moreover, numerical simulation is performed to show the typical gait pattern, and resonance phenomenon is observed. Finally, a preliminary experimental study is conducted to prove the validity of the mathematical model. The robot we developed and the mathematical model we derived enable further extensions on the gait analysis and model-based control by conveniently adopting efficient passivemimic walking techniques.

To better understand early brain development in health and disorder, it is critical to accurately segment infant brain magnetic resonance (MR) images into white matter (WM), gray matter (GM), and cerebrospinal fluid (CSF). Deep learning-based methods have achieved state-of-the-art performance; h owever, one of the major limitations is that the learning-based methods may suffer from the multi-site issue, that is, the models trained on a dataset from one site may not be applicable to the datasets acquired from other sites with different imaging protocols/scanners. To promote methodological development in the community, the iSeg-2019 challenge (http://iseg2019.web.unc.edu) provides a set of 6-month infant subjects from multiple sites with different protocols/scanners for the participating methods. T raining/validation subjects are from UNC (MAP) and testing subjects are from UNC/UMN (BCP), Stanford University, and Emory University. By the time of writing, there are 30 automatic segmentation methods participated in the iSeg-2019. In this article, 8 top-ranked methods were reviewed by detailing their pipelines/implementations, presenting experimental results, and evaluating performance across different sites in terms of whole brain, regions of interest, and gyral landmark curves. We further pointed out their limitations and possible directions for addressing the multi-site issue. We find that multi-site consistency is still an open issue. We hope that the multi-site dataset in the iSeg-2019 and this review article will attract more researchers to address the challenging and critical multi-site issue in practice.

After occasional perturbation, it is crucial to spontaneously control the limit cycle walking so that it quickly returns to its closed orbit in phase space. Otherwise, its stability can not be sufficiently guaranteed if the speed of recovery is slow while successive perturbation is applied. The accumulated deviation may eventually drive the phase outside the basin of attraction, leading to failure of the walking. In this sense, a control law that quickly recovers the disturbed phase before encountering the following perturbations is indispensable. With this consideration, here we analytically derive an optimal fast entrainment waveform that maximizes the speed of phase recovery based on phase reduction theory. Our theoretical method is numerically evaluated using a limit cycle walker, which is indirectly controlled by the oscillation of a wobbling mass via entrainment effect. The obtained waveform is used as the desired trajectory of the wobbling motion. The simulation results show that the waveform we derived achieves the best performance among all candidates. Our method helps to enhance the stability of limit cycle walking.

With the purpose of achieving stable and energy efficient locomotion on the slippery road surface, a sliding locomotion robot without joint torque but indirectly controlled by an active wobbling mass is recently proposed. In this paper, we deepen the analysis of the mechanism of the indirectly controlled sliding locomotion for further optimization and generalization. First, we derive the equations of dynamics and control. Second, we estimate the natural frequency of the robot, the moving speed and energy efficiency are also evaluated with respect to forcing amplitude and frequency of the wobbling mass. Third, the Arnol'd tongue is introduced to analyze the relationship between achieving efficient locomotion and being entrained. In addition, phase oscillation and synchronization phenomenon are analyzed via hysteresis plot to further interpret the unusual shapes of the Arnol'd tongues. Finally, we analyze the entrained, however, inefficient locomotion by reconfirming the rolling constraints from the mechanical energy dissipation point of view. Our results help better understanding of the indirectly controlling mechanism, and the methods can be applied to other indirectly controlled locomotion robots.

Precisely manipulating the center of mass (CoM) of the underactuated locomotion robot can't be easily achieved by common control mechanisms which apply only joint torques. A novel and indirect method has been recently introduced using an active wobbling mass attached to limit cycle walkers. The next important issue is to design an optimal control input to reduce the forcing energy. In this paper, we use combined rimless wheels as a simplified example to apply our method, which is based on the theory of phase oscillators. First, we introduce the typical modeling and control of this underactuated robot. Second, we obtain the phase response curve by numerically applying perturbations at different phases of the walker's gait interval and calculating the deviations from the unperturbed. Third, we analytically derive an optimal forcing waveform for the wobbling mass to entrain the combined rimless wheel based on the phase response curve. As an ecological extension, an ideal forcing waveform for m: 1 entrainment was further generated. Finally, the proposed method was evaluated by locking range of the Arnold tongues. The results show that the optimal forcing waveform we derived achieves the best performance for 1:1 entrainment among all the candidates. One of the strongest advantages of our method is the easiness of its implementation, prompting its applicability to a wide variety of locomotion systems.