با سلام خدمت کاربران در صورتی که با خطای سیستم پرداخت بانکی مواجه شدید از طریق کارت به کارت (6037997535328901 بانک ملی ناصر خنجری ) مقاله خود را دریافت کنید (تا مشکل رفع گردد).
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Six degree-of-freedom body-fixed hovering over unmapped asteroids via LIDAR altimetry and reinforcement meta-learning
حرکات ثابت شش درجه آزادی بدن بر روی سیارک های غیرقابل نقشه از طریق ارتفاع سنجی LIDAR و تقویت یادگیری متقابل-2020 We optimize a six degrees of freedom hovering policy using reinforcement meta-learning. The policy maps flash
LIDAR measurements directly to on/off spacecraft body-frame thrust commands, allowing hovering at a fixed
position and attitude in the asteroid body-fixed reference frame. Importantly, the policy does not require position
and velocity estimates, and can operate in environments with unknown dynamics, and without an asteroid
shape model or navigation aids. Indeed, during optimization the agent is confronted with a new randomly
generated asteroid for each episode, insuring that it does not learn an asteroids shape, texture, or environmental
dynamics. This allows the deployed policy to generalize well to novel asteroid characteristics, which we demonstrate
in our experiments. Moreover, our experiments show that the optimized policy adapts to actuator
failure and sensor noise. Although the policy is optimized using randomly generated synthetic asteroids, it is
tested on two shape models from actual asteroids: Bennu and Itokawa. We find that the policy generalizes well to
these shape models. The hovering controller has the potential to simplify mission planning by allowing asteroid
body-fixed hovering immediately upon the spacecrafts arrival to an asteroid. This in turn simplifies shape model
generation and allows resource mapping via remote sensing immediately upon arrival at the target asteroid. Keywords: Reinforcement learning | Asteroid missions | Hovering artificial intelligence | Autonomous maneuvers |
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