Mechanical impedance can be quite useful in robotic processing of objects. It represents properties of the material being processed. Robotic tasks that handle inhomogeneous material may be controled based on impedance information. This paper addresses impedance estimation in a mechanical processing task that employs a robot. The method uses existing motion sensors and actuator current sensing for robot “effort” in computing mechanical impedance, and fuzzy logic for interpretation of the impedance information. A Kalman filter is developed to estimate mechanical impedance based on a mathematical model of a joint drive-motor, in the time domain. A parameter identification method is utilized to estimate impedance parameters based on a process impedance model in the frequency domain. Impedance information, in both time domain and frequency domain, is interpreted for use in high level task control employing fuzzy logic and fuzzy associative memory. The technique is applied to a robotic fish processing system in the Industrial Automation Laboratory.