Designing a bipedal robot is a complex and challenging task, especially when dealing with a multitude of structural parameters. Traditional design methods often rely on human intuition and experience. However, such approaches are time-consuming, labor-intensive, lack theoretical guidance and hard to obtain optimal design results within vast design spaces, thus failing to full exploit the inherent performance potential of robots. In this context, this paper introduces the SERL (Structure Evolution Reinforcement Learning) algorithm, which combines reinforcement learning for locomotion tasks with evolution algorithms. The aim is to identify the optimal parameter combinations within a given multidimensional design space. Through the SERL algorithm, we successfully designed a bipedal robot named Wow Orin, where the optimal leg length are obtained through optimization based on body structure and motor torque. We have experimentally validated the effectiveness of the SERL algorithm, which is capable of optimizing the best structure within specified design space and task conditions. Additionally, to assess the performance gap between our designed robot and the current state-of-the-art robots, we compared Wow Orin with mainstream bipedal robots Cassie and Unitree H1. A series of experimental results demonstrate the Outstanding energy efficiency and performance of Wow Orin, further validating the feasibility of applying the SERL algorithm to practical design.

In its debut in the industry MLPerf benchmarks, NVIDIA Orin, a low-power system-on-chip based on the NVIDIA Ampere architecture, set new records in AI inference, raising the bar in per-accelerator performance at the edge. Overall, NVIDIA with its partners continued to show the highest performance and broadest ecosystem for running all machine-learning workloads and scenarios in this fifth round of the industry metric for production AI. In edge AI, a pre-production version of our NVIDIA Orin led in five of six performance tests. It ran up to 5x faster than our previous generation Jetson AGX Xavier, while delivering an average of 2x better energy efficiency. NVIDIA Orin is available today in the NVIDIA Jetson AGX Orin developer kit for robotics and autonomous systems.

NVIDIA has launched a follow-up to the Jetson AGX Xavier, its $1,100 AI brain for robots that it released back in 2018. The new module, called the Jetson AGX Orin, has six times the processing power of Xavier even though it has the same form factor and can still fit in the palm of one's hand. NVIDIA designed Orin to be an « energy-efficient AI supercomputer » meant for use in robotics, autonomous and medical devices, as well as edge AI applications that may seem impossible at the moment. The chipmaker says Orin is capable of 200 trillion operations per second. It's built on the NVIDIA Ampere architecture GPU, features Arm Cortex-A78AE CPUs and comes with next-gen deep learning and vision accelerators, giving it the ability to run multiple AI applications.

You can't keep a fitness company down. Following some rough financial news from one of the companies that thrived during the pandemic as many took up at-home workouts, Peloton is looking to bounce back, like a burpee, but more business-like. It just announced the Peloton Guide, a strength-training camera system that looks like Kinect, hooks up to your TV and uses machine learning to understand your movements. The movement tracker feature is compatible with hundreds of existing Peloton strength classes. The idea is to encourage users to carry out all of the exercises in a class and keep up with instructors (but it's not a big deal if you can't stick to the instructor's pace).

NVIDIA has launched a follow-up to the Jetson AGX Xavier, its $1,100 AI brain for robots that it released back in 2018. The new module, called the Jetson AGX Orin, has six times the processing power of Xavier even though it has the same form factor and can still fit in the palm of one's hand. NVIDIA designed Orin to be an "energy-efficient AI supercomputer" meant for use in robotics, autonomous and medical devices, as well as edge AI applications that may seem impossible at the moment. The chipmaker says Orin is capable of 200 trillion operations per second. It's built on the NVIDIA Ampere architecture GPU, features Arm Cortex-A78AE CPUs and comes with next-gen deep learning and vision accelerators, giving it the ability to run multiple AI applications. Orin will give users access to the company's software and tools, including the NVIDIA Isaac Sim scalable robotics simulation application, which enables photorealistic, physically-accurate virtual environments where developers can test and manage their AI-powered robots.

While NVIDIA's SoC efforts haven't gone entirely to plan since the company first started on them over a decade ago, NVIDIA has been able to find a niche that works in the automotive field. Backing the company's powerful DRIVE hardware, these SoCs have become increasingly specialized as the DRIVE platform itself evolves to meet the needs of the slowly maturing market for the brains behind self-driving cars. And now, NVIDIA's family of automotive SoCs is growing once again, with the formal unveiling of the Orin SoC. First outlined as part of NVIDIA's DRIVE roadmap at GTC 2018, NVIDIA CEO Jensen Huang took the stage at GTC China this morning to properly introduce the chip that will be powering the next generation of the DRIVE platform. Officially dubbed the NVIDIA DRIVE AGX Orin, the new chip will eventually succeed NVIDIA's currently shipping Xavier SoC, which has been available for about the last year now.

At the company's GPU Technology Conference (GTC) in Suzhou, China, Nvidia CEO Jensen Huang took to the stage to introduce Drive AGX Orin, the next generation SoC in the company's automotive portfolio. Orin follows Drive AGX Xavier, launched just under 2 years ago at CES 2018. Xavier is Nvidia's current flagship SoC for AI acceleration in vehicles. Orin, at 17 billion transistors, is almost double the size of Xavier, which had 9 billion, and it offers nearly 7x the performance (200 TOPS for INT8 data). Despite its size, Orin also offers 3x the power efficiency of Xavier, the company said.

At Nvidia's GTC Technology Conference in China this week, the chipmaker unveiled its latest NVIDIA DRIVE platform the AGX Orin. Orin is an advanced processor for autonomous vehicles or robots that was a result of four years of R&D investment by Nvidia. The new platform is powered by a new system-on-a-chip (SoC), which consists of 17 billion transistors. The Orin SoC integrates NVIDIA's next-generation GPU architecture and Arm Hercules CPU cores, combined with new deep learning and computer vision accelerators that can deliver 200 trillion operations per second (200 TOPS), which Nvidia says is 7 times better performance than the company's previous generation Xavier SoC, which delivers 30TOPS of performance. Orin can transmit over 200 gigabytes of data per second of data using just 60 to 70 Watts of power, according to Danny Shapiro, Nvidia's senior director of automotive.

Nvidia on Tuesday unveiled Orin, a new system-on-a-chip (SoC) designed for autonomous vehicles and robots, as well as a new software-defined platform powered by the SoC, called Nvidia Drive AGX Orin. Orin comes about two years after Nvidia debuted Xavier, its previous SoC for autonomous driving and robots. Consisting of 17 billion transistors, the new SoC offers nearly 7x the performance of Xavier, the company says. Anyone developing on Xavier today will be able to run their code on Orin, Nvidia said. Both are programmable through open CUDA and TensorRT APIs and libraries.