Autonomous systems are now crucial for commercial recovery and prosperity as businesses reel from labour shortages and changes in habits exacerbated by pandemic restrictions. But all agree that vital progress is too slow, with the autonomous vehicle (AV) industry growing particularly frustrated by the prohibitive cost and excessive timeframes of obtaining real-world data.
Simulated environments offer a solution, but the key to success will be in unlocking cost-effective AV guidance. LiDAR is expensive, camera-based systems are susceptible to failure and interference, and GPS can suffer from scintillation (interference caused by solar flares). mmWave radar simulation represents a commercially viable addition, and could be a key sensor for the future of autonomous vehicles.
This Innovation Briefing explores the benefits of using radar simulation to speed up, add confidence in and cut development costs of a radar sensing array. We also reveal the suitability of mmWave radar simulation to handle wider use cases, unlock reduced autonomous machine costs and enable greater levels of autonomy in the future.
専門家
Paolo is an experienced real-time embedded software engineering lead and has been helping clients achieve their ambitions by designing and delivering technical innovations for a wide range of applications in numerous sectors.
