The Active Neural SLAM model consists of three modules: a Global Policy, a Local Policy and a Neural SLAM Module. As shown below, the Neural-SLAM module predicts a map and agent pose estimate from incoming RGB observations and sensor readings. This map and pose are used by a Global policy to output a long-term goal, which is converted to a short-term goal using an analytic path planner. A Local Policy is trained to navigate to this short-term goal.
github地址：https://github.com/devendrachaplot/Neural-SLAM/
包含预训练模型地址