Inertial State Research Articles

Disjointness of inertial KMS states and the role of Lorentz symmetry in thermalization

For any local, translation-covariant quantum field theory on Minkowski spacetime, we prove that two distinct states that are invariant under the inertial time evolutions in different inertial reference frames are disjoint, i.e. neither state is a perturbation of the other, if the states are primary, have separating Gelfand–Naimark–Segal (GNS) vectors, and satisfy a timelike cluster property called the mixing property. These conditions are fulfilled by the inertial Kubo–Martin–Schwinger (KMS) states of the free scalar field, thus showing that a state satisfying the KMS condition relative to one inertial frame is far from thermal equilibrium relative to other inertial frames. We review the property of return to equilibrium (RTE) in open quantum systems theory and discuss the implications of disjointness on the asymptotic behavior of detector systems coupled to states of a free massless scalar field. We argue that the coupled system of an Unruh–DeWitt detector moving with constant velocity relative to the field in a KMS state, or an excitation thereof, cannot thermalize under generic conditions. This leads to an illustration of the physical differences between heat baths in inertial systems and the alleged “heat bath” of the Unruh effect. This paper also sketches the construction and RTE property of the quantum dynamical system of an Unruh–DeWitt detector coupled to a massless scalar field in a KMS state relative to the inertial rest frame of the detector.

EVI‐SAM: Robust, Real‐Time, Tightly‐Coupled Event–Visual–Inertial State Estimation and 3D Dense Mapping

EVI‐SAM: Robust, Real‐Time, Tightly‐Coupled Event–Visual–Inertial State Estimation and 3D Dense Mapping

An observer's perspective of the Unruh and Hawking effects—Using coherent signals to extract information from a black hole

The Unruh effect is one of the first calculations that explain what one would see when transiting between an inertial reference frame in its quantum field vacuum state and a non-inertial (specifically, uniformly accelerating) reference frame. The inertial reference frame's vacuum state would not correspond to the vacuum state of the non-inertial frame. The observer in the non-inertial frame would see radiation, with a corresponding Bose distribution and a temperature proportional to the acceleration. In this paper, I compute the response of this non-inertial observer to a single frequency mode in the inertial frame and deduce that, indeed, the cumulative distribution (over the observer's proper time) of frequencies observed by the accelerating observer would be the Bose distribution with a temperature proportional to the acceleration. The conclusion is that the Unruh effect (and the related Hawking effect) is generic, in that it would appear with any incoming incoherent state and the Bose distribution is obtained as a consequence of the non-inertial frame's motion, rather than some special property of the quantum vacuum. As a consequence of the analysis of a coherent set of signals, I show how to extract information from the spectrum that an accelerated observer would see (as well as from the radiation from a black hole).

Design of visual inertial state estimator for autonomous systems via multi-sensor fusion approach

Design of visual inertial state estimator for autonomous systems via multi-sensor fusion approach

Versatile LiDAR-Inertial Odometry With SE(2) Constraints for Ground Vehicles

LiDAR SLAM has become one of the major localization systems for ground vehicles since LiDAR Odometry And Mapping (LOAM). Many extension works on LOAM mainly leverage one specific constraint to improve the performance, <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">e.g.</i> , information from on-board sensors such as loop closure and inertial state; prior conditions such as ground level and motion dynamics. In many robotic applications, these conditions are often known partially, hence a SLAM system can be a comprehensive problem due to the existence of numerous constraints. Therefore, we can achieve a better SLAM result by fusing them properly. In this paper, we propose a hybrid LiDAR-inertial SLAM framework that leverages both the on-board perception system and prior information such as motion dynamics to improve localization performance. In particular, we consider the case for ground vehicles, which are commonly used for autonomous driving and warehouse logistics. We present a computationally efficient LiDAR-inertial odometry method that directly parameterizes ground vehicle poses on SE(2). The out-of-SE(2) motion perturbations are not neglected but incorporated into an integrated noise term of a novel SE(2)-constraints model. For odometric measurement processing, we propose a versatile, tightly coupled LiDAR-inertial odometry to achieve better pose estimation than traditional LiDAR odometry. Thorough experiments are performed to evaluate our proposed method's performance in different scenarios, including localization for both indoor and outdoor environments. The proposed method achieves superior performance in accuracy and robustness.

Adaptive fault‐tolerant attitude tracking control for hypersonic vehicle with unknown inertial matrix and states constraints

AbstractThis paper proposes an adaptive fault‐tolerant control (FTC) method for hypersonic vehicle (HSV) with unexpected centroid shift, actuator fault, time‐varying full state constraints, and input saturation. The occurrence of unexpected centroid shift has three main effects on the HSV system, which are system uncertainties, eccentric moments, and variation of input matrix. In order to ensure the time‐varying state constraints, a novel attitude state constraint control strategy, to keep the safe flight of HSV, is technically proposed by a time‐varying state constraint function (TVSCF). A unified controller is designed to handle the time‐varying state constraints according to the proposed TVSCF. Then, the constrained HSV system can be transformed into a novel free‐constrained system based on the TVSCF. For the variation of system input matrix, input saturation and actuator fault, a special Nussbaum‐type function is designed to compensate for those time‐varying nonlinear terms. Additionally, the auxiliary systems is designed to compensate the constraint of system control inputs. Then, it is proved that the proposed control scheme can guarantee the boundedness of all closed‐loop signals based on the Lyapunov stability theory. At last, the simulation results are provided to demonstrate the effectiveness of the proposed fault‐tolerant control scheme.

Distributed Absolute and Relative Estimation of Spacecraft Formations

For optimal decision making and collaborative task performance in multispacecraft missions, it is essential for each spacecraft to maintain a state estimate of all the spacecraft in the formation. However, especially in the case of large formation sizes, each spacecraft may not be able to track or communicate with all other spacecraft. Further, for formations deployed in deep space, the unavailability of the Global Navigation Satellite System makes inertial state estimation challenging. We propose the Distributed Absolute and Relative Estimation (DARE) algorithm for autonomous inertial estimation of spacecraft formations. The algorithm enables each spacecraft to maintain an accurate inertial estimate of the entire formation even in the presence of observability and communication constraints. Each spacecraft utilizes measurements of feature points (landmarks) for inertial localization and measurements of neighboring spacecraft for relative localization. The algorithm is distributed and scalable to any number of spacecraft in the formation. A modified version of the algorithm called the Sparse Distributed Absolute and Relative Estimation (SDARE) algorithm is also derived. This algorithm is computationally more efficient at the expense of estimation accuracy, making it suitable for implementation on nanosatellites where resources are limited. Numerical simulation results demonstrating the effectiveness and comparing the performance of both algorithms are provided.

Adaptive Fault-Tolerant Tracking Control of Quadrotor UAVs against Uncertainties of Inertial Matrices and State Constraints

This paper presents a study on a quadrotor unmanned aerial vehicle (UAV) fault-tolerant control scheme. According to the attitude model and safety control of the aircraft under the uncertainty of inertial matrix, the attitude state constraint by reinforcement learning is designed to ensure safety. Even if the boundary is crossed, it can be pulled back to the boundary by means of a designed penalty function with reinforcement learning. Meanwhile, in order to inhibit the oscillation caused by immediate reward as usual, an adaptive update law is proposed. Furthermore, considering the coupled actuator fault and system input saturation due to uncertainty of inertial matrix, the Nussbaum-type function is utilized in this work to handle this challenge, which likely causes the singularity of inertia matrix. As a consequence, combined with the Lyapunov stability theory, it is confirmed that the proposed FTC scheme ensures that all the closed-loop signals are bounded. Simulation results are carried out to illustrate the effectiveness and advantage of the proposed control scheme.

Radiation-free and non-Hermitian topology inertial defect states of on-chip magnons

Radiative damping is a strong dissipation source for the quantum emitters hybridized with propagating photons, electrons, or phonons, which is not easily avoidable for on-chip magnonic emitters as well that can radiate via the surface acoustic waves of the substrate. Here we demonstrate in an array of on-chip nanomagnets coupled in a long range via exchanging the surface acoustic waves that a point defect in the array, which can be introduced by the local magnon frequency shift by a local biased magnetic field or the absence of a magnetic wire, strongly localizes the magnons, in contrast to the well spreading Bloch-like collective magnon modes in such an array setting. The radiation of the magnon defect states is exponentially suppressed by the distance of the defect to the array edges. Moreover, this defect state is strikingly inertial to the non-Hermitian topology that localizes all the extended states at one boundary. Such configuration robust magnon defect states towards radiation-free limit may be suitable for high-fidelity magnon quantum information storage in the future on-chip magnonic devices.

Square-Root Extended Information Filter for Visual-Inertial Odometry for Planetary Landing

A novel sequential information filter formulation for computationally efficient visual-inertial odometry and mapping is developed in this work and applied to a realistic moon landing scenario. Careful construction of the square-root information matrix, in contrast to the full information or covariance matrix, provides easy and exact mean and covariance recovery throughout operation. Compared to an equivalent extended Kalman filter implementation, which provides identical results, the proposed filter does not require explicit marginalization of past landmark states to maintain constant-time complexity. Whereas measurements to opportunistic visual features only provide relative state information, resulting in drift over time unless a priori mapped landmarks are identified and tracked, the tight coupling of the inertial measurement unit provides some inertial state information. The results are presented in a terrain-relative navigation simulation for both a purely orbital case (with no active propulsion) and a landing case with a constant thrust.

MODULATION OF THE CENTER OF MASS DURING AN AGILITY TASK

PURPOSE: The control of the center of mass (COM) of the body may have implications for injury and performance in athletes. This study aimed to identify potential factors that modulate the COM during an agility task. METHODS: Fifty college (n = 28) and high school (n = 22) female soccer players had the displacement of retro-reflective markers placed over select bony landmarks recorded using a 20-camera motion analysis system while performing a modified T-test. Using the transverse plane positional histories of the markers, the peak change in the linear momentum vector (ΔLMV) of the COM of the pelvis and the angle (ΔLMVA) it formed with the laboratory X or Y axis entering and exiting the two 90 degrees turns performed at the center cone were obtained. The step pattern and extremity used to make the turns were determined. A linear mixed model was used to compare the effects of turn number, limb, step pattern and playing level on the peak ΔLMV and ΔLMVA. RESULTS: An effect (p < .01) of turn number on the ΔLMV and ΔLMVA were noted. The ΔLMV entering turn 1 and 2 was -66.5 (± 3.5) and -8.7 (± 3.5) kg*m/s, respectively and exiting turn 1 and 2 they were 32.9 (± 3.4) and 40.8 (± 3.4) kg*m/s, respectively. The ΔLMVA entering turn 1 and 2 were 6 (± 2) and -24 (± 2) deg, respectively and exiting turn 1 and 2 they were 56 (± 2) and -67 (± 2) deg, respectively. An effect (p = .03) of step pattern on the ΔLMV exiting the turn was noted. The ΔLMV was 42.4 (± 3.8) and 34.1 (± 3.1) kg*m/s, for multi-step and single step patterns, respectively. Playing level and leg dominance did not influence the ΔLMV and ΔLMVA. CONCLUSIONS: The initial inertial state of the COM appears to be the primary factor affecting the control of the COM entering and exiting a turn. When exiting a turn, the step pattern used entering the turn appears to also affect the control of the COM.

Stable Cavitation Interferes with Aβ16-22 Oligomerization.

Ultrasound and microbubbles are used for many medical applications nowadays. Scanning ultrasound can remove amyloid-β (Aβ) aggregates in the mouse brain and restores memory in an Alzheimer's disease mouse model. In vitro studies showed that amyloid fibrils are fragmented due to the ultrasound-induced bubble inertial cavitation, and ultrasonic pulses accelerate the depolymerization of Aβ fibrils into monomers at 1 μM of concentration. Under applied ultrasound, microbubbles can be in a stable oscillating state or unstable inertial cavitation state. The latter occurs when ultrasound causes a dramatic change of bubble sizes above a certain acoustic pressure. We have developed and implemented a nonequilibrium molecular dynamics simulation algorithm to the AMBER package, to facilitate the investigation of the molecular mechanism of Aβ oligomerization under stable cavitation. Our results indicated that stable cavitation not only inhibited oligomeric formation, but also prevented the formation of β-rich oligomers. The network analysis of state transitions revealed that stable cavitation altered the oligomerization pathways of Aβ16-22 peptides. Our simulation tool may be applied to optimize the experimental conditions to achieve the best therapeutical effect.

Analysis of the Composite Structure of the Cornea‐Contact Lens Assembly in Orthokeratology

AbstractContact lenses are currently a practical and effective solution for the correction of refractive errors but also for the application of orthokeratology procedures in cases of keratoconus or high myopia pathologies. In orthokeratology procedures, the contact lenses used are rigid (hard) and are made of biocompatible materials resulting in a composite structure together with the cornea of the human eye. Thus, the contact lenses for orthokeratology have the effect of deforming the corneal surface, in the latter inducing a series of residual and inertial stress states through which changes in the refractive power of the entire eyeball are obtained. This paper presents aspects related to the approach of the corneal‐contact lens composite structure as a thin curved plate set. Also, the study is completed with the determination of the different aspects in section and an anisotropic structure which implies an approach of biomechanical behavioral analyzes both in terms of the elastic component and the viscosity component manifested in the corneal structure. As shown by specialists, the cornea topography is determined by the balanced state between the internal and external forces acting on it and its mechanical rigidity, which is, in turn, defined by the cornea geometry, the biomaterial thickness, and rigidity. Therefore, the development of studies on the corneal‐contact lens combination in orthokeratology as a composite structure is closest to the real behavior of the whole.

Relaminarization of spanwise-rotating viscoelastic plane Couette flow via a transition sequence from a drag-reduced inertial to a drag-enhanced elasto-inertial turbulent flow

Direct numerical simulation of spanwise-rotation-driven flow transitions in viscoelastic plane Couette flow from a drag-reduced inertial to a drag-enhanced elasto-inertial turbulent flow state followed by full relaminarization is reported for the first time. Specifically, this novel flow transition begins with a drag-reduced inertial turbulent flow state at a low rotation number $0\leqslant Ro \leqslant 0.1$ , and then transitions to a rotation/polymer-additive-driven drag-enhanced inertial turbulent regime, $0.1\leqslant Ro \leqslant 0.3$ . In turn, the flow transitions to a drag-enhanced elasto-inertial turbulent state, $0.3\leqslant Ro \leqslant 0.9$ , and eventually relaminarizes at $Ro=1$ . In addition, two novel rotation-dependent drag enhancement mechanisms are proposed and substantiated. (1) The formation of large-scale roll cells results in enhanced convective momentum transport along with significant polymer elongation and stress generated in the extensionally dominated flow between adjacent roll cells at $Ro\leqslant 0.2$ . (2) Coriolis-force-generated turbulent vortices cause strong incoherent transport and homogenization of significant polymer stress in the bulk via their vortical circulations at $Ro=0.5 - 0.9$ .

Holism as the empirical significance of symmetries

Not all symmetries are on a par. For instance, within Newtonian mechanics, we seem to have a good grasp on the empirical significance of boosts, by applying it to subsystems. This is exemplified by the thought experiment known as Galileo’s ship: the inertial state of motion of a ship is immaterial to how events unfold in the cabin, but is registered in the values of relational quantities such as the distance and velocity of the ship relative to the shore. But the significance of gauge symmetries seems less clear. For example, can gauge transformations in Yang-Mills theory—taken as mere descriptive redundancy—exhibit a similar relational empirical significance as the boosts of Galileo’s ship? This question has been debated in the last fifteen years in philosophy of physics. I will argue that the answer is ‘yes’, but only for a finite subset of gauge transformations, and under special conditions. Under those conditions, we can mathematically identify empirical significance with a failure of supervenience: the state of the Universe is not uniquely determined by the intrinsic state of its isolated subsystems. Empirical significance is therefore encoded in those relations between subsystems that stand apart from their intrinsic states.

Run Your Visual-Inertial Odometry on NVIDIA Jetson: Benchmark Tests on a Micro Aerial Vehicle

This letter presents benchmark tests of various visual(-inertial) odometry algorithms on NVIDIA Jetson platforms. The compared algorithms include mono and stereo, covering Visual Odometry (VO) and Visual-Inertial Odometry (VIO): VINS-Mono, VINS-Fusion, Kimera, ALVIO, Stereo-MSCKF, ORB-SLAM2 stereo, and ROVIO. As these methods are mainly used for unmanned aerial vehicles (UAVs), they must perform well in situations where the size of the processing board and weight is limited. Jetson boards released by NVIDIA satisfy these constraints as they have a sufficiently powerful central processing unit (CPU) and graphics processing unit (GPU) for image processing. However, in existing studies, the performance of Jetson boards as a processing platform for executing VO/VIO has not been compared extensively in terms of the usage of computing resources and accuracy. Therefore, this study compares representative VO/VIO algorithms on several NVIDIA Jetson platforms, namely NVIDIA Jetson TX2, Xavier NX, and AGX Xavier, and introduces a novel dataset `KAIST VIO dataset' for UAVs. Including pure rotations, the dataset has several geometric trajectories that are harsh to visual(-inertial) state estimation. The evaluation is performed in terms of the accuracy of estimated odometry, CPU usage, and memory usage on various Jetson boards, algorithms, and trajectories. We present the results of the comprehensive benchmark test and release the dataset for the computer vision and robotics applications.

Multiple-model adaptive control architecture for a quadrotor with constant unknown mass and inertia

This paper proposes an architecture based on a multiple-model solution for height and yaw control of a quadrotor transporting an unknown constant load, added before the flight. Estimates of the inertial parameters (mass and z-axis inertia) and state variables (vertical position, velocity, yaw angle and rate) are obtained using data from the onboard sensors. A Multiple-Model Adaptive Controller (MMAC) architecture is proposed. The control of each partial model is based on a steady state Linear Quadratic Regulator (LQR), using integrative action for the height control. The resulting system is validated with load variations of up to 10% of the vehicle mass, both in simulation and experimentally, resorting to an off-the-shelf commercially available quadrotor.

In-flight positional and energy use data set of a DJI Matrice 100 quadcopter for small package delivery

We autonomously directed a small quadcopter package delivery Uncrewed Aerial Vehicle (UAV) or “drone” to take off, fly a specified route, and land for a total of 209 flights while varying a set of operational parameters. The vehicle was equipped with onboard sensors, including GPS, IMU, voltage and current sensors, and an ultrasonic anemometer, to collect high-resolution data on the inertial states, wind speed, and power consumption. Operational parameters, such as commanded ground speed, payload, and cruise altitude, were varied for each flight. This large data set has a total flight time of 10 hours and 45 minutes and was collected from April to October of 2019 covering a total distance of approximately 65 kilometers. The data collected were validated by comparing flights with similar operational parameters. We believe these data will be of great interest to the research and industrial communities, who can use the data to improve UAV designs, safety, and energy efficiency, as well as advance the physical understanding of in-flight operations for package delivery drones.

ОСНОВНІ СТАДІЇ ТА ЗАКОНОМІРНОСТІ ФОРМУВАННЯ БЕРЕГІВ ВЕЛИКИХ РІВНИННИХ ВОДОСХОВИЩ

The main stages of the reservoir coast formation and their typological characteristics are considered on the base of the analysis of long-term monitoring studies of the Dnieper reservoirs coast dynamics, as well as generalization of published materials on other large plain reservoirs. It is shown that the common scheme of periodization of the shoreline development manifested itself only in the two stages: abrasion and abrasion-accumulative leveling, and therefore it is premature to claim the general stabilization of the coast formation process. The conventionality of the dynamic equilibrium stage for the coast of reservoirs and the growing role of coastal currents and associated sediment flows and dynamic coast systems are noted. The current state of the coasts of large plain reservoirs is estimated as the beginning of the stabilization phase on the coasts with sufficient sand materials. On the coasts composed of loess, clay or loams the processes of intensive transformation are continued. The analysis of the direction of development of the coastal zone showed three stages of change of shore profile and plan: intensive formation, stabilization and the final stage of attenuation according to the leading factors. Active accumulation means the transition to the stage of abrasion-accumulative leveling, and the emergence of dynamic coast systems and activation of coastal sediment flows means the transition to the dismemberment of the shoreline by accumulative forms. The main regularities of development of coast formation processes – heredity, direction, inertia and variability are analyzed. The heredity means that the geographical and geological conditions which developed before the filling of the reservoir are played the leading role in these processes. The direction of development is associated with an increase of the erosion base and its consequence – the leveling of the coastal zone relief. The orientation of the general process of coast formation to achieve a state of dynamic equilibrium includes stages of inertia and variability. Inertial states are the certain periods when a certain set of factors and conditions and corresponding to them type of coast prevails. Variability is a change in factors and conditions, as a result of which new types of shores or fluctuations in the characteristics of the coastal zone (movement of shoals and dynamic coastal systems, seasonal changes in shore profiles) are formed.

State of the Art in Vision-Based Localization Techniques for Autonomous Navigation Systems

Vision-based localization systems, namely visual odometry (VO) and visual inertial odometry (VIO), have attracted great attention recently. They are regarded as critical modules for building fully autonomous systems. The simplicity of visual and inertial state estimators, along with their applicability in resource-constrained platforms motivated robotic community to research and develop novel approaches that maximize their robustness and reliability. In this paper, we surveyed state-of-the-art VO and VIO approaches. In addition, studies related to localization in visually degraded environments are also reviewed. The reviewed VO techniques and related studies have been analyzed in terms of key design aspects including appearance, feature, and learning based approaches. On the other hand, research studies related to VIO have been categorized based on the degree and type of fusion process into loosely-coupled, semi-tightly coupled, or tightly-coupled approaches and filtering or optimization-based paradigms. This paper provides an overview of the main components of visual localization, key design aspects highlighting the pros and cons of each approach, and compares the latest research works in this field. Finally, a detailed discussion of the challenges associated with the reviewed approaches and future research considerations are formulated.