This paper presents a robotic training system that can exercise the user without bodily restraint, neither markers nor sensors are attached to the trainee. We developed the robot system that has a total of four mounted components: a laser sensor, a camera, a cushion, and an electric motor. This paper have showed the method used for determining whether the trainee was bending forward or backward while walking, and the extent of the tilt, using the recorded image of the back of the trainee's head. A characteristic of our software algorithms has been that the image was divided into 9 quadrants, and each quadrant undergoes Hough transformation. We have verified experimentally that by using our algorithms for the four patterns of forward, backward, diagonally, and crouching, the tilt of the trainee's body have been accurately determined. We created a flowchart for determining the direction of movement according to experimental results. By adjusting the values used to make the distinction according to the position and the angle of the camera, and the width of the back of the trainee's head, we were able to accurately determine the walking condition of the trainee, and achieve early detection of the start of a fall.