Smooth Model Predictive Path Integral Control without Smoothing

We present a sampling-based control approach that can generate smooth actions for general nonlinear systems without external smoothing algorithms. Model Predictive Path Integral (MPPI) control has been utilized in numerous robotic applications due to its appealing characteristics to solve non-convex optimization problems. However, the stochastic nature of sampling-based methods can cause significant chattering in the resulting commands. Chattering becomes more prominent in cases where the environment changes rapidly, possibly even causing the MPPI to diverge. To address this issue, we propose a method that seamlessly combines MPPI with an input-lifting strategy. In addition, we introduce a new action cost to smooth control sequence during trajectory rollouts while preserving the information theoretic interpretation of MPPI, which was derived from non-affine dynamics. We validate our method in two nonlinear control tasks with neural network dynamics: a pendulum swing-up task and a challenging autonomous driving task. The experimental results demonstrate that our method outperforms the MPPI baselines with additionally applied smoothing algorithms.Comment: Accepted to IEEE Robotics and Automation Letters (and IROS 2022). Our video can be found at https://youtu.be/ibIks6ExGw

An Empirical Study on L2 Accents of Cross-lingual Text-to-Speech Systems via Vowel Space

With the recent developments in cross-lingual Text-to-Speech (TTS) systems, L2 (second-language, or foreign) accent problems arise. Moreover, running a subjective evaluation for such cross-lingual TTS systems is troublesome. The vowel space analysis, which is often utilized to explore various aspects of language including L2 accents, is a great alternative analysis tool. In this study, we apply the vowel space analysis method to explore L2 accents of cross-lingual TTS systems. Through the vowel space analysis, we observe the three followings: a) a parallel architecture (Glow-TTS) is less L2-accented than an auto-regressive one (Tacotron); b) L2 accents are more dominant in non-shared vowels in a language pair; and c) L2 accents of cross-lingual TTS systems share some phenomena with those of human L2 learners. Our findings imply that it is necessary for TTS systems to handle each language pair differently, depending on their linguistic characteristics such as non-shared vowels. They also hint that we can further incorporate linguistics knowledge in developing cross-lingual TTS systems.Comment: Submitted to ICASSP 202

Synergetic Influence of Microcrystalline Quartz and Alkali Content in Aggregate on Deterioration of Concrete Railroad Ties Used for 15 Years in High-Speed Railways

This study investigated the deteriorations of precast prestressed concrete (PSC) ties that were used for 15 years in high-speed railways in Korea and its damaging mechanism. The collected PSC ties with longitudinal cracks on sides and map cracks on surfaces exhibited strength degradation. The deteriorations were likely related to alkali-silica reaction (ASR) and delayed ettringite formation (DEF) together, given that the presence of massive ettringite crystals and the decomposition of ASR gel were found from microstructural analyses. Although there were no typical reactive siliceous aggregates for ASR in this study, ASR cracks were generated in the PSC ties. This is because the aggregates in the PSC ties with cracks were potentially reactive, and its high alkali-silica reactivity was likely attributable to the presence of microcrystalline quartz, supplying reactive SiO2 to trigger ASR. Furthermore, the alkali content in aggregates was associated with the deterioration of the PSC ties. The alkali-bearing minerals in aggregates (i.e., alkali feldspars) likely supplied enough alkalis for ASR. Besides, micas in aggregates could promote ASR due to their porous structure, which helps easy water ingress

Self-Supervised 3D Traversability Estimation With Proxy Bank Guidance

Traversability estimation for mobile robots in off-road environments requires more than conventional semantic segmentation used in constrained environments like on-road conditions. Recently, approaches to learning a traversability estimation from past driving experiences in a self-supervised manner are arising as they can significantly reduce human labeling costs and labeling errors. However, the self-supervised data only provide supervision for the actually traversed regions, resulting in epistemic uncertainty due to the lack of knowledge on non-traversable regions, also referred to as negative data. Negative data can rarely be collected as the system can be severely damaged while logging the data. To mitigate the uncertainty in the estimation, we introduce a deep metric learning-based method to incorporate unlabeled data with a few positive and negative prototypes. Our method jointly learns binary segmentation that reduces uncertainty in addition to the regression of traversability. To firmly evaluate the proposed framework, we introduce a new evaluation metric that comprehensively evaluates the segmentation and regression. Additionally, we construct a driving dataset ‘Dtrail’ in off-road environments with a mobile robot platform, which is composed of numerous complex and diverse representations of off-road environments. We examine our method on Dtrail as well as the publicly available SemanticKITTI dataset

Importance of active layer positioning on gate electrode in organic thin-film transistors

International audienceWe describe the importance of active layer positioning for a gate electrode in organic thin-film transistors (TFTs). For this study, we utilizea numerical simulation based on 2-D Atlas, which is a two-dimensional technology computer aided design (so called 2D TCAD) software tool created by Silvaco. Variation in the electrical characteristics of pentacene TFTs is systematically explored by changing the mismatch length (L M) between the active layer and gate electrode in the bottomgate top-contact configuration. It is found that as the L M increases, the electrical performance of pentacene TFTs is exponentially degraded in terms of drain current on/off characteristics. In particular, we explain this phenomenon by examining variations in charge distribution and gate electric field in the TFT channel region byincreasing the L M

Experimental and computational study on mechanical analysis of mesh-type lightweight design for binder-jet 3D printing

3D printing technology has recently been highlighted as an innovative manufacturing process. Among various 3D printing methods, a binder jetting (BJ) 3D printing is particularly known as a technology to produce the complex sand mold quickly for a casting process. However, high manufacturing cost, due to its expensive materials, needs to be lowered for more industrial applications of 3D printing. In this study, we investigated mechanical properties of sand molds with a lightweight structure for low material consumption and short process time. Our stress analysis using a computational approach revealed a structural weak point in a mesh-type lightweight design applied to the 3D-printed ceramic-polymer composite.Published versio

Numerical Analysis on Effective Mass and Traps Density Dependence of Electrical Characteristics of a-IGZO Thin-Film Transistors

We have investigated the effect of electron effective mass (me*) and tail acceptor-like edge traps density (NTA) on the electrical characteristics of amorphous-InGaZnO (a-IGZO) thin-film transistors (TFTs) through numerical simulation. To examine the credibility of our simulation, we found that by adjusting me* to 0.34 of the free electron mass (mo), we can preferentially derive the experimentally obtained electrical properties of conventional a-IGZO TFTs through our simulation. Our initial simulation considered the effect of me* on the electrical characteristics independent of NTA. We varied the me* value while not changing the other variables related to traps density not dependent on it. As me* was incremented to 0.44 mo, the field-effect mobility (µfe) and the on-state current (Ion) decreased due to the higher sub-gap scattering based on electron capture behavior. However, the threshold voltage (Vth) was not significantly changed due to fixed effective acceptor-like traps (NTA). In reality, since the magnitude of NTA was affected by the magnitude of me*, we controlled me* together with NTA value as a secondary simulation. As the magnitude of both me* and NTA increased, µfe and Ion deceased showing the same phenomena as the first simulation. The magnitude of Vth was higher when compared to the first simulation due to the lower conductivity in the channel. In this regard, our simulation methods showed that controlling me* and NTA simultaneously would be expected to predict and optimize the electrical characteristics of a-IGZO TFTs more precisely

Photoswitchable Microgels for Dynamic Macrophage Modulation

Dynamic manipulation of supramolecular self-assembled structures is achieved irreversibly or under non-physiological conditions, thereby limiting their biomedical, environmental, and catalysis applicability. In this study, microgels composed of azobenzene derivatives stacked via pi-cation and pi-pi interactions are developed that are electrostatically stabilized with Arg-Gly-Asp (RGD)-bearing anionic polymers. Lateral swelling of RGD-bearing microgels occurs via cis-azobenzene formation mediated by near-infrared-light-upconverted ultraviolet light, which disrupts intermolecular interactions on the visible-light-absorbing upconversion-nanoparticle-coated materials. Real-time imaging and molecular dynamics simulations demonstrate the deswelling of RGD-bearing microgels via visible-light-mediated trans-azobenzene formation. Near-infrared light can induce in situ swelling of RGD-bearing microgels to increase RGD availability and trigger release of loaded interleukin-4, which facilitates the adhesion structure assembly linked with pro-regenerative polarization of host macrophages. In contrast, visible light can induce deswelling of RGD-bearing microgels to decrease RGD availability that suppresses macrophage adhesion that yields pro-inflammatory polarization. These microgels exhibit high stability and non-toxicity. Versatile use of ligands and protein delivery can offer cytocompatible and photoswitchable manipulability of diverse host cells