Today's autonomous robots are being tasked with increasingly important and dynamic roles across industries. From the autonomous mobile robots (AMRs) that move goods around warehouses to the drones that handle last-mile delivery, these devices are trusted to operate at the edge with little direct human oversight or handling. These robots rely heavily on the sensors that enable them to perceive, understand, and interact with the world around them. As edge AI models are brought in to support more ...
Humanoid robots are already moving totes in major logistics warehouses, sequencing parts on automotive assembly lines, and running pilots in some of the world's largest fulfillment centers. The first wave has landed, not in labs or demos, but in production environments doing real work. And, with Goldman Sachs projecting the market to reach $38 billion by 2035, the platforms being designed today are the ones that will scale into that growth. But building a humanoid is not like building a convent...
Present-day edge AI systems rely heavily on multi-modal sensor fusion, such as camera, lidar, and radar, to enable accurate, real-time decision-making. Existing platforms, such as NVIDIA® Jetson Orin NX, are equipped to adequately support multi-camera use cases. To advance this further, NVIDIA’s latest Jetson Thor series modules have been combined with the Holoscan Sensor Bridge board – running on a Lattice FPGA – to address the increase in sensor counts and synchronization...
Interest in edge computing has surged as organizations across industries seek smarter ways to automate processes, enhance productivity, and optimize labor. By processing data closer to its source, edge systems can provide benefits like reduced transmission and storage costs and strengthened security. They can also enable the development of advanced machines and devices, from autonomous mobile robots (AMRs) and humanoids to smart medical devices, which can operate with precision and speed. Thes...
Across industries and use cases, computing capacity is shifting away from centralized servers and towards the edge. Whether in the form of autonomous vehicles, smart sensors, or other technological solutions, today's intelligent applications demand faster decision-making and increased autonomy. This shift is especially prevalent in the Industrial, defense, and aerospace industries. The unmanned aerial vehicles (UAVs) and drones used in defense applications rely heavily on edge intelligence to...