Do More with Less: Single-Model, Multi-Goal Architectures for Resource-Constrained Robots
Zili Wang,Drew Threatt,Sean B. Andersson,Roberto Tron,Zili Wang,Drew Threatt,Sean B. Andersson,Roberto Tron
Deep learning methods are widely used in robotic applications. By learning from prior experience, the robot can abstract knowledge of the environment, and use this knowledge to accomplish different goals, such as object search, frontier exploration, or scene understanding, with a smaller amount of resources than might be needed without that knowledge. Most existing methods typically require a sign...
