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We study the Kalman Filter for the linear elastic wave equation over the real line with spatially distributed partial state measurements. The dynamics of the filter are described by a spatial convolution operator with asymptotic exponential spatial decay rate. This decay rate dictates how measurements from different spatial locations must be exchanged to implement the filter: faster spatial decay implies local measurements are more relevant and the filter is more “decentralized”; slower decay implies farther measurements also become relevant and the filter is more “centralized”. Using dimensional analysis, we demonstrate that this decay rate is a function of one dimensionless group defined from system parameters, such as wave speed and noise variances. We find a critical value of such dimensionless group for which the Kalman Filter is completely decentralized.

We propose a new neck design for legged robots to achieve robust visual-inertial state estimation in dynamic locomotion. While visual-inertial state estimation is widely used in robotics, it has a problem of being disturbed by the impacts and vibration generated when legged robots move dynamically. The use of rubber dampers may be a solution, but even if the dampers are proper for some gaits, they may be excessively deformed or resonated at certain frequencies during other gait locomotion since they are not tunable. To address this problem, we develop a tunable neck system that absorbs the impacts and vibration during diverse gait locomotions. This neck system consists of two components: 1) a suspension mechanism that compensates for the weight of the head equipped with a camera and IMU (inertial measurement unit), absorbs the impacts and the head motion of high frequencies including vibration as a fixed low-pass filter; and 2) a dynamic vibration absorber (DVA) that can be reactively-adjusted to diverse gait frequencies to alleviate excessive head movements. We present a dynamics analysis of the neck system and show how to adjust the target frequency of the system. Simulation and experimental validation are performed to verify the effect of the proposed neck design, manifesting superior estimation performance and robustness across diverse gaits.

The ability to process environment maps across multiple sessions is critical for robots operating over extended periods of time. Specifically, it is desirable for autonomous agents to detect changes amongst maps of different sessions so as to gain a conflict-free understanding of the current environment. In this letter, we look into the problem of change detection based on a novel map representation, dubbed Plane Signed Distance Fields (PlaneSDF), where dense maps are represented as a collection of planes and their associated geometric components in SDF volumes. Given point clouds of the source and target scenes, we propose a three-step PlaneSDF-based change detection approach: (1) PlaneSDF volumes are instantiated within each scene and registered across scenes using plane poses; 2D height maps and object maps are extracted per volume via height projection and connected component analysis. (2) Height maps are compared and intersected with the object map to produce a 2D change location mask for changed object candidates in the source scene. (3) 3D geometric validation is performed using SDF-derived features per object candidate for change mask refinement. We evaluate our approach on both synthetic and real-world datasets and demonstrate its effectiveness via the task of changed object detection.

We developed an environmentally adaptive under‐ice navigation framework that was deployed in the Arctic Beaufort Sea during the United States Navy Ice Exercise in March 2020 (ICEX20). This navigation framework contained two subsystems developed from the ground up: (1) an on‐board hydrodynamic model‐aided navigation (HydroMAN) engine, and (2) an environmentally and acoustically adaptive integrated communication and navigation network (ICNN) that provided acoustic navigation aiding to the former. The HydroMAN synthesized measurements from an inertial navigation system (INS), ice‐tracking Doppler velocity log (DVL), ICNN and pressure sensor into its self‐calibrating vehicle flight dynamic model to compute the navigation solution. The ICNN system, which consisted of four ice buoys outfitted with acoustic modems, trilaterated the vehicle position using the one‐way‐travel‐times (OWTT) of acoustic datagrams transmitted by the autonomous underwater vehicle (AUV) and received by the ice buoy network. The ICNN digested salinity and temperature information to provide model‐assisted real‐time OWTT range conversion to deliver accurate acoustic navigation updates to the HydroMAN. To decouple the contributions from the HydroMAN and ICNN subsystems towards a stable navigation solution, this article evaluates them separately: (1) HydroMAN was compared against DVL bottom‐track aided INS during pre‐ICEX20 engineering trials where both systems provided similar accuracy; (2) ICNN was evaluated by conducting a static experiment in the Arctic where the ICNN navigation updates were compared against GPS with ICNN error within low tens of meters. The joint HydroMAN‐ICNN framework was tested during ICEX20, which provided a nondiverging high‐resolution navigation solution—with the majority of error below 15 m—that facilitated a successful AUV recovery through a small ice hole after an 11 km untethered run in the upper and mid‐water column.

In this review, recent trends in microelectronics packaging reliability are summarized. We review the technology from early packaging concepts, including wire bond and BGA, to advanced techniques used in HI schemes such as 3D stacking, interposers, fan-out packaging, and more recently developed silicon interconnect fabric integration. This review includes approaches for both design modification studies and packaged device validation. Methods are explored for compatibility in new complex packaging assemblies. Suggestions are proposed for optimizations of the testing practices to account for the challenges anticipated in upcoming HI packaging schemes.

Adding fiducial markers to a scene is a well-known strategy for making visual localization algorithms more robust. Traditionally, these marker locations are selected by humans who are familiar with visual localization techniques. This paper explores the problem of automatic marker placement within a scene. Specifically, given a predetermined set of markers and a scene model, we compute optimized marker positions within the scene that can improve accuracy in visual localization. Our main contribution is a novel framework for modeling camera localizability that incorporates both natural scene features and artificial fiducial markers added to the scene. We present optimized marker placement (OMP), a greedy algorithm that is based on the camera localizability framework. We have also designed a simulation framework for testing marker placement algorithms on 3D models and images generated from synthetic scenes. We have evaluated OMP within this testbed and demonstrate an improvement in the localization rate by up to 20 percent on four different scenes.

This paper presents normalizing flows for incremental smoothing and mapping (NF-iSAM), a novel algorithm for inferring the full posterior distribution in SLAM problems with nonlinear measurement models and non-Gaussian factors. NF-iSAM exploits the expressive power of neural networks, and trains normalizing flows to model and sample the full posterior. By leveraging the Bayes tree, NF-iSAM enables efficient incremental updates similar to iSAM2, albeit in the more challenging non-Gaussian setting. We demonstrate the advantages of NF-iSAM over state-of-the-art point and distribution estimation algorithms using range-only SLAM problems with data association ambiguity. NF-iSAM presents superior accuracy in describing the posterior beliefs of continuous variables (e.g., position) and discrete variables (e.g., data association).

Conventional discontinuous pulse width modulation (DPWM) strategies for cascaded H-bridge static compensators suffer from poor inter-phase capacitor voltage balance control during unbalanced grid voltage conditions. Specifically, the logic-based algorithm that calculates the zero-sequence voltage (ZSV) for discontinuous operation interacts with the closed-loop capacitor voltage control. This paper proposes an optimal DPWM strategy based on a finite-set optimization that chooses the best ZSV candidate that minimizes the control interactions while clamping a converter voltage. Furthermore, the effect of the different ZSV candidates on the switching loss is also considered within the optimization. Extensive experimental study is provided to demonstrate the effectiveness of the proposed approach.

A critical reduction in the total harmonic distortion in the output voltage of multilevel inverters can be obtained with an appropriate selection of the angles to switch the power semiconductors at low frequency. Among the methods used to obtain the required sequence of angles, it is possible to recognize both standard and optimized methods, like the Newton–Raphson method or the genetic algorithm, to mention a few. However, implementing the genetic algorithm implies using several configuration parameters, so it is difficult to know if the best option was chosen. This paper implements the Taguchi design of experiments, the Taguchi method, to obtain the appropriate switching angles for an multilevel inverter producing an output voltage of five and seven levels. Experimental results obtained from a laboratory prototype using the computed angles in the MATLAB GA solver demonstrate the superiority of the proposed method.