Google AI Blog: A Structured Approach to Unsupervised Depth Learning from Monocular Videos
Posted by Anelia Angelova, Research Scientist, Robotics at Google Perceiving the depth of a scene is an important task for an autonomous robot — the ability to accurately estimate how far from the robot objects are, is crucial for obstacle avoidance, safe planning and navigation. While depth can be obtained (and learned) from sensor data, such as LIDAR, it is also possible to learn it in an unsupe
Teaching Robots to Understand Semantic Concepts
Posted by Sergey Levine, Faculty Advisor and Pierre Sermanet, Research Scientist, Google Brain Team Machine learning can allow robots to acquire complex skills, such as grasping and opening doors. However, learning these skills requires us to manually program reward functions that the robots then attempt to optimize. In contrast, people can understand the goal of a task just from watching someone
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