Efficient Perception

Efficient perception in robotics and computer vision aims to rapidly and accurately extract meaningful information from sensory data, minimizing computational cost and latency. Current research emphasizes developing resource-efficient algorithms, such as memory-efficient patch-based processing and neuromorphic approaches leveraging hardware acceleration, to handle high-resolution imagery and 3D data streams from diverse sensors (e.g., cameras, lidar). These advancements are crucial for enabling real-time performance in applications like autonomous driving, robotic manipulation, and search-and-rescue, where swift and accurate perception is paramount. The integration of semantic information and active learning strategies further enhances efficiency by focusing processing on relevant data and reducing unnecessary computations.