Within a perception framework for autonomous mobile and robotic systems, semantic analysis of 3D point clouds typically generated by LiDARs is key to numerous applications, such as object detection and recognition, and scene reconstruction. Scene semantic segmentation can be achieved by directly integrating 3D spatial data with specialized deep neural networks. Although this type of data provides rich geometric information regarding the surrounding environment, it also presents numerous challenges: its unstructured and sparse nature, its unpredictable size, and its demanding computational requirements. These characteristics hinder the real-time semantic analysis, particularly on resource-constrained hardware architectures that constitute the main computational components of numerous robotic applications. Therefore, in this paper, we investigate various 3D semantic segmentation methodologies and analyze their performance and capabilities for resource-constrained inference on embedded NVIDIA Jetson platforms. We evaluate them for a fair comparison through a standardized training protocol and data augmentations, providing benchmark results on the Jetson AGX Orin and AGX Xavier series for two large-scale outdoor datasets: SemanticKITTI and nuScenes.

A million developers across the globe are now using the NVIDIA Jetson platform for edge AI and robotics to build innovative technologies. Plus, more than 6,000 companies -- a third of which are startups -- have integrated the platform with their products. These milestones and more will be celebrated during the NVIDIA Jetson Edge AI Developer Days at GTC, a global conference for the era of AI and the metaverse, taking place online March 20-23. Register free to learn more about the Jetson platform and begin developing the next generation of edge AI and robotics. Atlanta-based Kris Kersey, the mind behind the popular YouTube channel Kersey Fabrications, is one developer using the NVIDIA Jetson platform for his one-in-a-million technological innovations.

Nvidia, leading manufacturer of AI-enabled processor technology, and embedded specialist Syslogic are entering into a strategic partnership. The new addition is a Syslogic component by Nvidia's partner program Jetson Ecosystem. Nvidia lists companies that promote the development of products based on the Jetson platform and thus pave the way for AI applications. Thanks to the new partnership with Syslogic, Nvidia's processor technology will be increasingly used in the rough industrial environments. As an AI pioneer Nvidia currently offers three processor families with different performance capabilities with its Jetson platform - Jetson Nano, Jetson TX2 and Jetson AGX Xavier.

Nvidia unveiled its Jetson TX2 platform to power drones with good artificial intelligence. The platform includes the Jetson TX2 "embedded AI supercomputer," a chip and its surruonding hardware that can power 4K video drones that consume only about 7.5 watts of power. Drones with the TX2 solution can operate two cameras simultaneously. The Jetson 3.0 platform was designed for AI "at the edge" of the network, rather than in the cloud, or Internet-connected data center. Drones with cameras can capture a huge amount of data. This means Jetson has to handle a lot of the processing of data at the edge, in the device itself, rather than transferring all of that data to the cloud, said Deepu Talla, vice president and general manager of Nvidia's Tegra business unit, at a press event in San Francisco.