Chapter 14: Sensors and Perception: Sensor Data Processing and Filtering
Abstract : Sensor data processing and filtering" refers to the process of taking raw data collected from sensors, cleaning it up, removing unwanted noise or inconsistencies, and transforming it into a usable format for further analysis and interpretation , essentially allowing a system to accurately "perceive" its environment based on the sensor inputs. Key points about sensor data processing and filtering: Raw data: Sensors produce raw data, which can be affected by noise, errors, and inconsistencies due to environmental factors or sensor limitations. Cleaning and Preprocessing: The first step is to clean the raw data by removing outliers, correcting for known biases, and applying calibration factors. Filtering Techniques: Low-pass filters: Remove high-frequency noise while preserving the overall trend of the data. High-pass filters: Remove low-frequency noise while preserving rapid changes in the data. Bandpass filters: ...