Tsinghua University

Assembly Line

TsFile: A Standard Format for IoT Time Series Data

📅 Date:

✍️ Author: Susan Hall

🔖 Topics: Data Architecture, IIoT, Open Source

🏢 Organizations: Apache Software Foundation, Tsinghua University

TsFile is a columnar storage file format designed for time series data, featuring advanced compression to minimize storage, high throughput of read and write, and deep integration with processing and analysis tools such as Apache projects Spark and Flink. TsFile is designed to support a “high ingestion rate up to tens of million data points per second and rare updates only for the correction of low-quality data; compact data packaging and deep compression for long-live historical data; traditional sequential and conditional query, complex exploratory query, signal processing, data mining and machine learning.”

TsFile is the underlying storage file format for the Apache IoTDB time-series database. IoTDB represents more than a decade of work at China’s Tsinghua University School of Software. It became a top-level project with the Apache Software Foundation in 2020.

Read more at The New Stack

DiffuseBot: Breeding Soft Robots With Physics-Augmented Generative Diffusion Models

📅 Date:

✍️ Authors: Tsun-Hsuan Wang, Juntian Zheng, Pingchuan Ma

🏢 Organizations: MIT, Tsinghua University

Nature evolves creatures with a high complexity of morphological and behavioral intelligence, meanwhile computational methods lag in approaching that diversity and efficacy. Co-optimization of artificial creatures’ morphology and control in silico shows promise for applications in physical soft robotics and virtual character creation; such approaches, however, require developing new learning algorithms that can reason about function atop pure structure. In this paper, we present DiffuseBot, a physics-augmented diffusion model that generates soft robot morphologies capable of excelling in a wide spectrum of tasks. DiffuseBot bridges the gap between virtually generated content and physical utility by (i) augmenting the diffusion process with a physical dynamical simulation which provides a certificate of performance, and ii) introducing a co-design procedure that jointly optimizes physical design and control by leveraging information about physical sensitivities from differentiable simulation. We showcase a range of simulated and fabricated robots along with their capabilities.

Read more at Open Review