10-Hz beads pellet injection and laser engagement

Laser Inertial Fusion Energy reactor requires repetitive fuel pellet injection and laser engagement to fuse fusion fuel beyond a few Hz. We demonstrate 10 Hz free-fall bead pellets injection and laser engagement with γ-ray generation. Diameter of 1 mm deuterated polystyrene beads were engaged by counter illuminating ultra-intense laser pulses with intensity of 5 x1017 W/cm2 at 10 Hz. The spatial distribution of free-fall beads was 0.86 mm in horizontal, and 0.18 mm in vertical. The system operated beyond 5 minute, 3500 beads supply with achieved frequencies of 2.1 Hz for illumination on bead and 0.7 Hz for γ-ray generation, these frequencies increments three times in relation to the previous 1 Hz injection system. The operation duration was limited by pellet supply. This injection and engagement system can apply for Laser Inertial Fusion Energy research platform.

Fast Attitude Estimation System for Unmanned Ground Vehicle Based on Vision/Inertial Fusion

The attitude estimation system based on vision/inertial fusion is of vital importance and great urgency for unmanned ground vehicles (UGVs) in GNSS-challenged/denied environments. This paper aims to develop a fast vision/inertial fusion system to estimate attitude; which can provide attitude estimation for UGVs during long endurance. The core idea in this paper is to integrate the attitude estimated by continuous vision with the inertial pre-integration results based on optimization. Considering that the time-consuming nature of the classical methods comes from the optimization and maintenance of 3D feature points in the back-end optimization thread, the continuous vision section calculates the attitude by image matching without reconstructing the environment. To tackle the cumulative error of the continuous vision and inertial pre-integration, the prior attitude information is introduced for correction, which is measured and labeled by an off-line fusion of multi-sensors. Experiments with the open-source datasets and in road environments have been carried out, and the results show that the average attitude errors are 1.11° and 1.96°, respectively. The road test results demonstrate that the processing time per frame is 24 ms, which shows that the proposed system improves the computational efficiency.