- Clearpath Announces TurtleBot 4
- AMD to Fuse FPGA AI Engines Onto EPYC Processors, Arrives in 2023
- Updating the CUDA Linux GPG Repository Key
- Arm debuts powerhouse Cortex-M processor
- Diagnostic Medical Ultrasound Innovation Using UltraFast Algorithms
- Nvidia starts laying groundwork for future open and parallel code
- India reveals plan to become major RISC-V design and production player by 2023
- Accelerating AI Robotics and Vision Equipment Deployment with NVIDIA Platforms
- Developing and Deploying AI-powered Robots with NVIDIA Isaac Sim and NVIDIA TAO
Source: IEEE Spectrum, May 4, 2022 
Open Robotics, iRobot, and Clearpath team up to deliver a rugged, flexible addition to the ROS 2 ecosystem
Source: Tom's Hardware, May 4, 2022 
AMD will use Xilinx's FPGA-powered AI inference engine in its processors. The first products are slated to arrive in 2023. AMD's recent patents indicate it is already well underway in enabling multiple methods of connecting AI accelerators to its processors, including using 3D chip stacking tech.
Source: NVIDIA Technical Blog, April 29, 2022 
NVIDIA is updating and rotating the signing keys used by the apt, dnf/yum, and zypper package managers beginning April 27, 2022. If you don't update your repository signing keys, expect package management errors when attempting to install packages from CUDA repositories.
Source: Edn, May 2, 2022 
The company is expanding its Arm Virtual Hardware to more platforms, including third-party devices, in an effort to make the IoT and embedded development process more accessible.
Source: Semiconductor Engineering, May 5, 2022 
AMD explores implementing very high data rate algorithms using adaptive computing architectures, in Diagnostic Medical Ultrasound Innovation Using UltraFast Algorithms.
Source: The Register, May 2, 2022 
Nvidia is stepping up its work with standards and open-source communities. A lot of work is being done specifically around programming languages like C++ and Fortran. The company's goal is to make generic computing environments more productive and approachable for coders.
Source: The Register, April 29, 2022 
India's government has announced a plan and roadmap for local semiconductor design and production, based on the open source RISC-V architecture, and set a goal of delivering world-class silicon by the end of next year.
Source: Advantech, April 18, 2022 
AI is making advances in different industries due to its potential to increase the precision and efficiency of traditional robotics programming. In this video, Advantech and Techman Robot will explore applications that leverage AI robotics and vision equipment and the challenges associated their deployment.
Source: NVIDIA Technical Blog, May 3, 2022 
With the advent of AI, you can build even smarter robots that can better perceive their surroundings. The NVIDIA TAO Toolkit is a low-code AI model development solution with built-in transfer learning. It allows you to fine-tune a pretrained model with a fraction of the data compared to training from scratch.
Hardware Acceleration in Robotics Newsletters
- Hardware Acceleration in Robotics #7 - ROS 2 HAWG - meeting #8, ROS 2 Nodes for Perception, using NVIDIA Jetson to create real-time multi-camera pipelines and more
- Hardware Acceleration in Robotics #6 - ROS 2 Hardware Acceleration Architecture including cloud, Nav2 integration with NVIDIA Isaac ROS GEMs, RISC-V chip adoption and more
- Hardware Acceleration in Robotics #5 - Global robot software market to reach 7527 million $ in 2025, NVIDIA medical-grade chip with hardware acceleration and more
- Hardware Acceleration in Robotics #4 - Single-Chip Processors, a technical review of NVIDIA Jetson Orin and the new ROS 2 iRobot Create 3 and more
- Hardware Acceleration in Robotics #3 - Hardware-accelerated ROS 2 Pipelines, The Robotic Processing Unit (RPU) and more
- Hardware Acceleration in Robotics #2 - Nvidia Isaac ROS GEMs, Nvidia H100, updates to CUDA-X Libraries and more
- Hardware Acceleration in Robotics #1 - ROS2 for Self-Driving Cars, Intel world fastest FPGAs, Nvidia GTC and more
ROS 2 Hardware Acceleration Working Group meetings
- Hardware Acceleration WG, meeting #8
- Hardware Acceleration WG, meeting #7
- Hardware Acceleration WG, meeting #6
- Hardware Acceleration WG, meeting #5
- Hardware Acceleration WG, meeting #4
- Hardware Acceleration WG, meeting #3
- Hardware Acceleration WG, meeting #2
- Hardware Acceleration WG, meeting #1
Alcorn, P. (2022, May 4). AMD to fuse FPGA AI engines onto EPYC processors, arrives in 2023. Tom's Hardware. https://www.tomshardware.com/news/amd-to-fuse-fpga-ai-engines-onto-epyc-processors-arrives-in-2023 ↩︎
Armstrong, R., & Mittman, K. (2022, April 29). Updating the CUDA Linux GPG repository key. NVIDIA Technical Blog. https://developer.nvidia.com/blog/updating-the-cuda-linux-gpg-repository-key/ ↩︎
Nordyk, S. (2022, May 2). Arm debuts powerhouse Cortex-M processor. Edn. https://www.edn.com/arm-debuts-powerhouse-cortex-m-processor/ ↩︎
BHATTACHARYA, S. (2022, May 5). Diagnostic medical ultrasound innovation using ultrafast algorithms. Semiconductor Engineering. https://semiengineering.com/diagnostic-medical-ultrasound-innovation-using-ultrafast-algorithms/?cmid=05dc1e27-28ec-4b3f-9dfd-6f38857f7f23 ↩︎
Shah, A. (2022, May 2). Nvidia sees trillion-dollar future in open and parallel code. The Register: Enterprise Technology News and Analysis. https://www.theregister.com/2022/05/02/nvidia_open_standards/ ↩︎
Sharwood, S. (2022, April 29). India reveals RISC-V CPU roadmap, expects product by 2023. The Register: Enterprise Technology News and Analysis. https://www.theregister.com/2022/04/29/india_risc_v_microprocessor_program/ ↩︎
Accelerating AI robotics and vision equipment deployment with NVIDIA platforms. (2022, April 18). Advantech . https://www.advantech.com/resources/video/accelerating-ai-robotics-and-vision-equipment-deployment-with-nvidia-platforms ↩︎
Kulkarni, A., & Chadha, R. (2022, May 3). Developing and deploying AI-powered robots with NVIDIA Isaac Sim and NVIDIA TAO. NVIDIA Technical Blog. https://developer.nvidia.com/blog/developing-and-deploying-ai-powered-robots-with-nvidia-isaac-sim-and-nvidia-tao/ ↩︎