Antenna-like Sensors

In order to achieve versatile artificial perception–action systems, the walking machine should not only have sound tropism, but it should also perform other

52 4 Physical Sensors and Walking Machine Platforms

Inverting amplifier circuit

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Fig. 4.5. The basic scheme of the stereo auditory sensor system. The detected signals coming from the left and right microphones are initially amplified via the integrated amplifier circuit of the microphone. Then, amplified signals are scaled to a range between 0 and 5 volts through the support circuitry. After that, the MBoard digitizes the scaled output voltages to a 7-bit value, where 0 represents silence and 128 represents maximum volume. Eventually, the digital signals from the MBoard are displayed on a PC or a PDA via an RS232 interface at a transfer rate of 57.6 kbits/s

behaviors like an animal, e.g., wandering and avoiding objects or even escaping from a deadlock situation.

Therefore, additional sensors which can detect obstacles are required. In-spired by an insect antenna (cf. Chap. 2), our physical sensors were modeled using the infrared (IR) sensors. An IR sensor has a lot in common with an insect antenna. Although an IR sensor acts differently from an insect antenna, by measuring the brightness of the IR light reflected by objects, the result-ing measurement is the same. It is a well-known fact in robotics, that usresult-ing IR sensors instead of antennas is a simplification as well as a solution with low power consumption. Most researchers use the sensors in a mobile robot as well as in a walking machine for obstacle avoidance [72, 74, 128] or even wall following [46].

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Fig. 4.6. (a) The sound source is close to the fore left microphone. This results in the signal coming from the fore left microphone (dashed line) having high amplitude and it is followed by the signal coming from the rear right microphone (solid line) with a delay, while the reverse case is presented in (b). All figures have the same scale in thex-axis and they-axis

In this book, three types of the IR sensor, later called “antenna-like sen-sors”, were chosen to detect obstacles at distances of 4–30 cm, 10–80 cm and 20–150 cm. The antenna-like sensors were implemented and tested on two dif-ferent walking machines (four-legged and six-legged walking machines). Two antenna-like sensors which can detect obstacles at a distance of 10–80 cm were installed on the (moving) forehead of the four-legged walking machine AMOS-WD02.² They make an angle of approximately 25 degrees with respect to the horizontal body axis of the walking machine. The angle was manually ad-justed for optimal operation. Consequently, the walking machine is able to detect obstacles on the fore left and right of its body (Fig. 4.7).

As a result of the structure of the four-legged walking machine, its head, where the sensors were implemented, can vertically turn left and right with respect to the walking pattern by activating the backbone joint. Consequently, the sensors can also scan obstacles in a wider angle. In other words, they perform like an active antenna scanning an obstacle in two-dimensional space (Fig. 4.8).

Normally, two antenna-like sensors on its left and right foreheads are suf-ficient to perform an obstacle avoidance. However, to prevent the legs of the walking machines from hitting obstacles, like chair or desk legs, more sensors are needed and they can be installed on the (moving) legs.

Here, the six sensors were implemented on the six-legged walking machine AMOS-WD06. Two of them, which can detect the obstacle at a long distance of 20–150 cm, were fixated at the forehead while the rest of them, operating at a shorter distance 4–30 cm, were fixated at the two forelegs and two middle legs. The configuration of the sensors on the AMOS-WD06 and the idealized field of the sensors are presented in Fig. 4.9.

2 Advanced MObility Sensor driven-Walking Device.

54 4 Physical Sensors and Walking Machine Platforms

Fig. 4.7. The antenna-like sensors implemented on the forehead of the four-legged walking machine.Left: The outline of the sensors from a top view.Right: The real sensors fixated on the forehead of the physical four-legged walking machine AMOS-WD02 (arrows)

Fig. 4.8.The idealized field of the antenna-like sensors when the backbone joint of the walking machine is activated. Left: The outline of the idealized field where the sensors can scan obstacles (dashed curve). Right: The visualization of the sensors moving with the head of the walking machine when the backbone joint turns right (upper picture) and left (lower picture)

As shown in Fig. 4.9, one pair of the forehead sensors performs like a passive antenna detecting obstacles in front of the walking machine, while the other two pairs installed on the (moving) legs perform like active antennas because they move along the legs. Therefore, these (active) sensors can scan the obstacle in three-dimensional space; i.e., they move forward and backward

Fig. 4.9.Left: The visualization of the locations where the sensors are implemented and the idealized field of the sensors protecting the walking machine from crashing into obstacles (dashed linearound the walking machine).Right: The six sensors on the physical walking machine (arrows)

in parallel to the ground (Fig. 4.9) and they also move up and down in a vertical direction (Fig. 4.10).

To obtain the sensory data for controlling the behavior of the walking machine, all sensors were interfaced and digitized via the ADC channels of the MBoard at the sampling rate of up to 5.7 kHz. Subsequently, the digital signals are sent to either a PC or a PDA through an RS232 interface at a transfer rate of 57.6 kbits/s for the purpose of monitoring and feeding the data afterwards into the preprocessing network. The basic scheme of the sensor system is shown in Fig. 4.11.

The example of the sensor signals responding to a presented object is shown in Fig. 4.12. As shown in Fig. 4.12, the sensor signals have some noise resulting in uneven signals, and this may lead to difficulties in controlling the behavior of the walking machines. Therefore, the preprocessing of these sensor signals, described in Sect. 5.1.3, is required to eliminate the unwanted sensory noise and to trigger the obstacle avoidance behavior of the walking machines.