![]() □️īut these cars aren't just for racing. ![]() To train our autonomous controllers, we transformed our classroom at HQ into a simple racetrack, where we had volunteers manually drive the cars around to establish a human baseline that we could beat with our autonomous controllers. ![]() ![]() This effort is part of an IRAD project titled Sim2Real □ Our team successfully built a fleet of autonomous-capable 1/10th scale cars with a suite of sensors, including vision and LiDAR, designed after the MuSHR platform by the Personal Robotics Lab at the University of Washington. □□ #AI #Robotics #SafeRL #Innovation #Technology #Research Let's continue exploring the frontiers of AI, robotics, and Safe Reinforcement Learning. It underscores the need for human intervention in autonomous driving and offers valuable insights into creating autonomous systems for space missions, ultimately increasing mission efficiency. This research has broad implications, from autonomous systems to space missions. Crafting precise reward functions is key to teaching desired behaviors. □ Their findings highlight the risk of agent dependence on RTA and emphasize the importance of human intervention for AI system safety. By conducting ablation studies inspired by neurology experiments, the team uncovers the dynamics of SafeRL and its impact on learning and performance. Hamilton and his team celebrated their research on "Ablation Study of How Run Time Assurance Impacts the Training and Performance of Reinforcement Learning Agents." This study dives into the growing importance of reinforcement learning (RL) and the role of run-time assurance (RTA). at Vanderbilt University, where he explored "Safe and Robust Reinforcement Learning for Autonomous Cyber-Physical Systems." His research drew inspiration from the need to incorporate safety into AI to increase reliability, particularly in situations like spacecraft docking and autonomous driving. Hamilton's journey began during his Ph.D. Hamilton's expertise lies in Safe Reinforcement Learning (SafeRL), an approach that prioritizes safety in AI solutions and is applicable across various domains. Nate Hamilton, an AI scientist at Parallax Advanced Research. □ Dive into the dynamic world of AI and robotics with insights from Dr. Soc., 75, 5-33.□ Unlocking Safe Autonomy: Dr. High-resolution satellite imagery for mesoscale meteorological studies. In reality, the anvil spread a little into Colorado. Both satellites misplace the southern edge of the anvil north of the border with Colorado. GOES 8, looking from the southeast, leaves the anvil well in Wyoming. GOES 9, looking at this storm from the southwest, misplaces the eastern edge of the anvil across the border into Nebraska. Look at the cumulonimbus anvil in the southeastern corner of Wyoming (this is the state in the upper left quadrant of the images). Two nearly simultaneous (1.5 minutes apart) satellite infrared images on 18 June 1997, from GOES 8 (top) and GOES 9 (bottom). Parallax displacement is important for high clouds such as cumulonimbus anvils ( Fig 3).įig 3. The direction of the apparent offset, of course, is directly away from the satellite, along a great circle arc from the subsatellite point. For a cloud at, say, 10 km altitude, at 60 ° latitude (and the same longitude as the satellite), the offset is just the height of the cloud multiplied by the normalized offset value from the graph, i.e. Normalized cloud offset for a geostationary satellite image, due to parallax induced cloud displacements. In examining the above schematic it should be noted that geostationary satellites orbit at 35,800 km above the Earth surface, whereas high clouds are at most 18 km above sea level.įig 2. The illustration comparing high to low clouds assumes that the satellite is 52 ° from the local zenith (Fig 2). High clouds are displaced further than low clouds. Illustration of the parallax displacement. This displacement, known as parallax, is more significant at places in the perimeter of the hemisphere viewed by a geostationary satellite, compared to those in the centre ( Fig 2).įig 1. If a satellite is far from the local zenith, or the satellite's viewing angle from nadir is large, clouds are displaced somewhat relative to the surface ( Fig 1). Parallax correction in satellite images Parallax correction in satellite images
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