Page 248 - Mechatronics for Safety, Security and Dependability in a New Era

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approach an elevator push the button wait for the opening

get on the elevator push the button inside get off the elevator
Figure 4: The mobile robot is taking an elevator.

Route Teaching
The robot needs a free space map and a destination or a route to perform a free movement. The
free space map is generated by the map generation capability of the robot, which is already embedded
(Miura, Negishi, and Shirai 2002). The destination may be given by some coordinate values, but they
are not intuitive for the user to teach. So we take the following "teaching by guiding" approach (Katsura
et al. 2003, Kidono, Miura, and Shirai 2002).
In route teaching, we first take the robot to a destination. During this guided movement, the robot
learns the route. Then the robot can reach the destination by localizing itself with respect to the learned
route. Such two-phase methods have been developed for both indoor and outdoor mobile robots; some
of them are map-based (Kidono, Miura, and Shirai 2002, Maeyama, Oya, and Yuta 1997) and some are
view-based (Katsura et al. 2003, Matsumoto, Inaba, and Inoue 1996).
In this work, the robot simply memorizes the trace of its guided movement. Although the estimated
trace suffers from accumulated errors, the robot can safely follow the learned route because of the reliable
map generation; the robot moves to the direction of the destination within the recognized free space.
The next problem is how to guide the robot. In Katsura et al. (2003) and Kidono, Miura, and Shirai
(2002), we used a joystick to control the robot; but this requires the user to know the mechanism of
the robot. A user-friendly way is to implement a person-following function to the robot (Huber and
Kortenkamp 1995, Sawano, Miura, and Shirai 2000). For a simple and reliable person detection, we use
a teaching device which has red LEDs; the user shows the device to the robot while he/she guides it to
the destination (see Fig. 5). The robot repeatedly detects the device in both of the two omnidirectional
camera by using a simple color-based detection algorithm, and calculates its relative position in the robot
coordinates. The calculated position is input to our path planning method (Negishi, Miura, and Shirai
2004) as a temporary destination. Fig. 6 shows a snapshot of person tracking during a guided movement.
Teaching of Vision-Based Operation
This section describes the methods for teaching the position of an elevator, the positions of buttons,
and the views of them.
Teaching the Elevator Position Suppose that the robot has already be taken to the elevator hall, using
the method described above. The robot then asks about the position of the elevator. The user indicates it
by pointing the door of the elevator (see Fig. 7). The robot has a general model of elevator shape, which
is mainly composed of two parallel lines corresponding to the wall and the elevator door projected onto
the floor. Using this model and the LRF (laser range finder) data, the robot searches the indicated area
for the elevator and sets the origin of the elevator local coordinates at the center of the gap of the wall in
front of the door (see Fig. 8).