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Shield AI Fundamentals: On Perception
What does perception refer to in robotic systems?
We’re referring to a robot’s ability to sense the environment around it, process the information that’s coming in from its sensors, and use it in order to perceive the environment, figure out where it is and how it’s operating relative to the environment, and leverage that information in order to make decisions or take actions.
Can you elaborate on what concepts fall within the overarching concept of perception?
We generally consider perception as including sensing, state estimation, mapping and localization.
Sensing refers to the robot’s ability to observe the environment around it, as well as its state within that environment, through the use of its onboard sensors.
State estimation is the process through which a robot determines its state based upon direct information from its sensors or inferences made given information from a combination of different sensors. A robot’s state is used to describe the status of the robot at any particular instance in time. It defines both where the robot is in the world — its position, orientation, linear velocities, angular accelerations, and so forth — and its internal characteristics, such as its battery levels and system wear-and-tear. State estimation allows a robot to understand where it is relative to the world around it.
Mapping refers to the robot’s ability to create a model of the world around it. There are many different ways of representing the environment, and mapping is the challenge of taking sensor observations and transforming them into a consistent environment representation. From an algorithmic perspective, it allows the robot to build an environment state model.
Localization refers to the robot’s ability to determine where it is relative to that environment model. The robot will build its map as it moves through the environment while figuring out where it is relative to that map that it’s building.
How do a robot’s sensors impact its perception?
A robot’s sensors provide it with information that allows the robot to model the world and its position within it. The fidelity of that model is directly contingent on the fidelity of the information.
What impact do environmental characteristics have on perception?
Environmental characteristics influence the information that a robot can perceive. It’s not hard to imagine that a robot that depends heavily on visual perception will have a tough time in dark or smoke or fog.