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Nanowatt all-optical 3D perception for mobile robotics

Tao Yan, Tiankuang Zhou, Yanchen Guo, Zhao Yun, Guocheng Shao, Jiamin Wu, Ruqi Huang, Qionghai Dai, Lu Fang

Year
2024
Citations
7

Abstract

Three-dimensional (3D) perception is vital to drive mobile robotics' progress toward intelligence. However, state-of-the-art 3D perception solutions require complicated postprocessing or point-by-point scanning, suffering computational burden, latency of tens of milliseconds, and additional power consumption. Here, we propose a parallel all-optical computational chipset 3D perception architecture (Aop3D) with nanowatt power and light speed. The 3D perception is executed during the light propagation over the passive chipset, and the captured light intensity distribution provides a direct reflection of the depth map, eliminating the need for extensive postprocessing. The prototype system of Aop3D is tested in various scenarios and deployed to a mobile robot, demonstrating unprecedented performance in distance detection and obstacle avoidance. Moreover, Aop3D works at a frame rate of 600 hertz and a power consumption of 33.3 nanowatts per meta-pixel experimentally. Our work is promising toward next-generation direct 3D perception techniques with light speed and high energy efficiency.

Keywords

RoboticsArtificial intelligenceComputer sciencePerceptionHuman–computer interactionComputer visionBiologyNeuroscienceRobot

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