Knowledge of soil properties and identifying worked soil type are critical for optimized control strategies of an autonomous excavator. The current paper presents an online soil type identification based on real-time measuring of energy components for horizontal dragging tasks. The online energy measurement, calculated by integration of the force acting on an object along a displacement, makes the resulting data robust to noise. Analysis of the energy measurement reveals that the correlation between potential—dissipation energy and displacement has unique characteristics for any given soil, independently of the amount of applied force. This leads to the creation of a new soil ‘energy map' with respect to various soil types. A mathematical model has been developed for each soil's ‘energy map'. An identification algorithm has been developed to utilize these prior mathematical models for cross-referencing with online total energy of the currently worked soil to identify soil type online. The overall approach has been validated experimentally on a laboratory test-rig using mulch, gravel, sand, and clay soils.
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