I see people are using a lot the terms sensing, perception, and learning together in the context of artificial intelligence. It seems to me perception is a more board term that may include sensing and learning. What are their definitions and how do they interact with each other? Any paper references are highly appreciated.
Sense and perceive, in robotics, are synonyms. There is no practical technological step between sensing and perception. If we take a robot for example, or in intelligent thermostat, the sensor signal is fed to the controller (or agent if we consider reinforcement learning), actions come out of controller (or agent). There is no in-between step practically which would constitute a difference between sensing and perception.
One could argue, that there is a difference between the sensor signal and the robots internal representation of state. If we consider SLAM algorithms or sensor fusion also in this case there is "no extra" step which one could call perception, differentiated from sensing.
Learning is a procedure, which uses data to create models. It is very loosely linked to sensing. Sensing can be used to gather data for learning and sensed data can be passed though a machine learning model to achieve a certain goal (e.g. classifying that signal or identifying an object if the signal is a camera).
The comments to the question are suggesting that perception would be somehow information derived from sensing...That is just signal processing, has been called that for years, the goal of signal processing is not to "create perception" but to process signals and derive other/better information from it.