Fitness is important to achieve day to day tasks in our lives. It is significantly more important for the elderly as the functionality of the body declines. Fullerton Fitness Test (FFT) is a set of exercises to assess the fitness of the elderly. It was developed at Fullerton University by Dr. Roberta Rikli and Dr. Jessie Jones as a part of the LifeSpan Wellness Program. Under FFT, an individual is asked to go through a certain range of motions and based on these motions, a physician assigns a score to each exercise in FFT. The individual’s fitness is assessed based on these scores. At present, FFT is performed in the presence of a trained physician. The overall goal of the research presented in this thesis is to assess an individual’s fitness using a depth sensor mounted differential drive robot based on FFT without the help of a physician as a trained physician might not be always available and even if one is available, having one around every time is expensive. The robot autonomously navigates through the testing facility, tracks the user, assists the user performing FFT and saves the data in user file for further evaluation. The results received from the FFT is evaluated to measure the performance of the user. This data is also used for book keeping purposes and to track the progress of the user. This research is also concerned with integrating this setup with a smart home facility where all the data is stored in a central server.