Authors:
Iván del Pino
;
Miguel Á. Muñoz-Bañón
;
Miguel Á. Contreras
;
Saúl Cova-Rocamora
;
Francisco A. Candelas
and
Fernando Torres
Affiliation:
Group of Automation, Robotics and Computer Vision (AUROVA), University of Alicante, San Vicente del Raspeig S/N, Alicante and Spain
Keyword(s):
Kalman Filter, SDKF, Speed Estimation, Speed Control, Incremental Rotary Encoder, Low-resolution, Low-cost, Mobile Robotics.
Related
Ontology
Subjects/Areas/Topics:
Adaptive Signal Processing and Control
;
Informatics in Control, Automation and Robotics
;
Mobile Robots and Autonomous Systems
;
Real-Time Systems Control
;
Robot Design, Development and Control
;
Robotics and Automation
;
Signal Processing, Sensors, Systems Modeling and Control
;
Vehicle Control Applications
Abstract:
In mobile robotics, the low-level control is a key component that translates the desires of the high-level system into actual voltages and currents to drive the motors. PID controllers have been extensively used for speed control, but their performance depend heavily on the quality of the process variable (PV) estimation. In fact, noise and outliers --if not properly filtered-- might lead to system instability. In this work, we present a speed estimation strategy that enables us to develop an inexpensive, accurate and easy-to-install speed control solution. The proposed system relies on a Hall effect sensor and a Single-Dimensional Kalman Filter and its suitability is demonstrated through a number of real experiments controlling the speed of an Unmanned Ground Vehicle. We detail the design, implementation and validation processes and provide a GitHub repository with the developed software and CAD designs.