Faced with strong demand for robots working in underwater pipeline environments, a novel underwater multi-model locomotion robot is designed and studied in this research. By mimicking the earthworms metameric body, the robot is segmented in the struc
ture; by synthesizing the earthworm-like peristaltic locomotion mechanism and the propeller-driven swimming mechanism, the robot possesses unique multi-mode locomotion capability. In detail, the in-pipe earthworm-like peristaltic crawling is achieved based on servomotor-driven cords and pre-bent spring-steel belts that work antagonistically, and the three-dimensional underwater swimming is realized by four independently-controlled propellers. With a robot covering made of silicon rubber, the two locomotion modes are tested in the underwater environment, through which, the rationality and the effectiveness of the robot design are demonstrated. Aiming at predicting the robotic locomotion performance, mechanical models of the robot are further developed. For the underwater swimming mode, by considering the robot as a spheroid, an equivalent dynamic model is constructed, whose validity is verified via computational fluid dynamics (CFD) simulations; for the in-pipe crawling mode, a classical kinematics model is employed to predict the average locomotion speeds under different gait controls. The outcomes of this research could offer useful design and modeling guidelines for the development of earthworm-like locomotion robots with unique underwater multi-mode locomotion capability.
Tactile sensing plays an important role in robotic perception and manipulation tasks. To overcome the real-world limitations of data collection, simulating tactile response in a virtual environment comes as a desirable direction of robotic research.
In this paper, we propose Elastic Interaction of Particles (EIP) for tactile simulation. Most existing works model the tactile sensor as a rigid multi-body, which is incapable of reflecting the elastic property of the tactile sensor as well as characterizing the fine-grained physical interaction between the two objects. By contrast, EIP models the tactile sensor as a group of coordinated particles, and the elastic property is applied to regulate the deformation of particles during contact. With the tactile simulation by EIP, we further propose a tactile-visual perception network that enables information fusion between tactile data and visual images. The perception network is based on a global-to-local fusion mechanism where multi-scale tactile features are aggregated to the corresponding local region of the visual modality with the guidance of tactile positions and directions. The fusion method exhibits superiority regarding the 3D geometric reconstruction task.
Spintronic diodes are emerging as disruptive candidates for impacting several technological applications ranging from the Internet of Things to Artificial Intelligence. In this letter, an overview of the recent achievements on spintronic diodes is br
iefly presented, underling the major breakthroughs that have led these devices to have the largest sensitivity measured up to date for a diode. For each class of spintronic diodes (passive, active, resonant, non-resonant), we indicate the remaining developments to improve the performances as well as the future directions. We also dedicate the last part of this perspective to new ideas for developing spintronic diodes in multiphysics systems by combining 2-dimensional materials and antiferromagnets.
Tactile sensing plays an important role in robotic perception and manipulation. To overcome the real-world limitations of data collection, simulating tactile response in virtual environment comes as a desire direction of robotic research. Most existi
ng works model the tactile sensor as a rigid multi-body, which is incapable of reflecting the elastic property of the tactile sensor as well as characterizing the fine-grained physical interaction between two objects. In this paper, we propose Elastic Interaction of Particles (EIP), a novel framework for tactile emulation. At its core, EIP models the tactile sensor as a group of coordinated particles, and the elastic theory is applied to regulate the deformation of particles during the contact process. The implementation of EIP is conducted from scratch, without resorting to any existing physics engine. Experiments to verify the effectiveness of our method have been carried out on two applications: robotic perception with tactile data and 3D geometric reconstruction by tactile-visual fusion. It is possible to open up a new vein for robotic tactile simulation, and contribute to various downstream robotic tasks.
With excellent folding-induced deformability and shape reconfigurability, origami-based designs have shown great potentials in developing deployable structures. Noting that origami deployment is essentially a dynamic process, while its dynamical beha
viors remain largely unexplored owing to the challenges in modeling. This research aims at advancing the state of the art of origami deployable structures by exploring the transient dynamics under free deployment, with the Miura-origami tube being selected as the object of study because it possesses relatively simple geometry, exceptional kinematic properties, and wide applications. In detail, a preliminary free deployment test is performed, which indicates that the transient oscillation in the transverse direction is nonnegligible and the tube deployment is no longer a single-degree-of-freedom (SDOF) mechanism. Based on experimental observations, four assumptions are made for modeling purposes, and a 2N-DOF dynamic model is established for an N-cell Miura-origami tube to predict the transient oscillations in both the deploying and the transverse directions. Employing the settling times and the overshoot values as the transient dynamic indexes, a comprehensive parameter study is then carried out. It reveals that both the physical and geometrical parameters will significantly affect the transient deploying dynamics, with some of the parameter dependence relationships being counter-intuitive. The results show that the relationships between the transient dynamic behaviors and the examined parameters are sometimes contradictory in the deploying and the transverse directions, suggesting the necessity of a compromise in design.
The harvesting of ambient radio-frequency (RF) energy is an attractive and clean way to realize the idea of self-powered electronics. Here we present a design for a microwave energy harvester based on a nanoscale spintronic diode (NSD). This diode co
ntains a magnetic tunnel junction with a canted magnetization of the free layer, and can convert RF energy over the frequency range from 100 MHz to 1.2 GHz into DC electric voltage. An attractive property of the developed NSD is the generation of an almost constant DC voltage in a wide range of frequencies of the external RF signals. We further show that the developed NSD provides sufficient DC voltage to power a low-power nanodevice - a black phosphorus photo-sensor. Our results demonstrate that the developed NSD could pave the way for using spintronic detectors as building blocks for self-powered nano-systems, such as implantable biomedical devices, wireless sensors, and portable electronics.
Microwave detectors based on the spin-transfer torque diode effect are among the key emerging spintronic devices. By utilizing the spin of electrons in addition to charge, they have the potential to overcome the theoretical performance limits of thei
r semiconductor (Schottky) counterparts, which cannot operate at low input power. Here, we demonstrate nanoscale microwave detectors exhibiting record-high detection sensitivity of 75400 mV mW$^{-1}$ at room temperature, without any external bias fields, for input microwave power down to 10 nW. This sensitivity is 20x and 6x larger than state-of-the-art Schottky diode detectors (3800 mV mW$^{-1}$) and existing spintronic diodes with >1000 Oe magnetic bias (12000 mV mW$^{-1}$), respectively. Micromagnetic simulations supported by microwave emission measurements reveal the essential role of the injection locking to achieve this sensitivity performance. The results enable dramatic improvements in the design of low input power microwave detectors, with wide-ranging applications in telecommunications, radars, and smart networks.
