Before presenting the parameter identification of the blimp altitude and planar movement nominal model (2.25) and (2.29), let us take a look at the sensors used for the blimp system which provide measurements for state estimation and control process.
The choice of sensors for the blimp robot system depends on various fac- tors, including the desired operations for the robot to achieve, the hardware restrictions (e.g. weight limit, energy limit, installation position and method), etc. Therefore it puts forward specified requirements on the measuring method, precision and frequency of the sensors.
On the other way, the information provided by the sensors also influences the observer and controller design for the blimp system, and leads to the success or failure of the blimp motion control task.
In this work, the studied blimp robot has a balloon which has an ellipsoid- like shape, with a length of 105cm, a width of 55cm, and the height is 71cm, it has a volume of about 0.2m3, when filled with helium, the balloon can carry a total weight of about 200 grams. The size of the blimp is miniature compared to other airships in the related works.
Notice that the 200 grams of payload has to include all the hardwares in- cluding gondola structure to fix the micro-controller board to the hull, the motors with propellers as the system actuators, the battery for power supply and wireless communication devices for the possibility of data exchange with host computer. Therefore only low weight sensors and actuators can be integrated in an embedded micro-system, which means the measurement of on-board sensors cannot be very accurate.
At first, for the design of the blimp robot prototype, the following sensors are chosen, as shown in Figure 2.4.
The IMU MPU-6050 (on the left of Figure 2.4) combines a MEMS 3-axis accelerometer and a 3-axis gyroscope in a miniature package, which can be used to estimate relative position, orientation, velocity and acceleration of the blimp [InvenSense, 2018]. But due to the integration of measurement (including error) to get position, the result suffers from drifting problem. Thus it is preferable to
2.5. Sensors 55
Figure 2.4 – Sensors used for NON-A blimp prototype: IMU MPU-6050 (left), US range finder LV-MaxSonar-EZ1 (middle), wireless camera ALM-2451G (right) only use the IMU measurements for orientation estimation, and relative position estimation during a short period.
It is worth to mention that the MPU-6050 is a low cost and light weight sensor, although digital filter is implemented inside the chip to eliminate high- frequency noise, the accuracy of the measurements is still limited. Hence, when using the sensor for yaw angle estimation (as the roll and pitch movements are ignored), the result is not satisfactory especially after long time. As one of the main advantages of the blimp robot is its long endurance in air and autonomous operation time, if the IMU MPU-6050 is the only source of information to determine the pose of the blimp, it will be hard to design powerful observer and controller to assure the performance of blimp motion control.
The US range finder is an active exteroceptive sensor which can measure directly the distance from the robot to its surrounding within the dispersal cone of the sensor. Thus it is an ideal complementary sensor to the IMU, and if possible, we can install multiple US sensors around the blimp robot pointing to different directions and get the relative position estimation of robot inside the environment.
However, the acceptable payload of the balloon only allows one of such sensor to be mounted, thus in the prototype of our blimp robot, one LV-MaxSonar-EZ1 USrange finder (on the middle of Figure 2.4) is installed vertically downward on the control board to measure the distance from robot to the ground (or other obstacles below the robot). The sensor gives readings from 0 to 255
56 CHAPTER 2. Modeling and Parameter Identification inches (0 to 6.45m) with a resolution of 1 inch (2.54cm) [MaxBotix, 2018]. In the parameter identification process, the US sensor is used to give altitude measurements (Section 2.6.1). But it is worth to mention that the dispersal cone of the sensor limits the precision of measurements and creates possible jumps during successive measurements, and the speed of sound limits the frequency of acquisition and introduces delay into the control loop.
As it is mentioned before, the visual sensors like cameras are powerful sensors which can provide enormous amount of environmental information in images. Hence, in the prototype of blimp robot, the wireless camera ALM-2451G (on the right of Figure 2.4) is mounted horizontally towards front on the gondola [Aliveal, 2018]. It is supposed to take pictures of the environment in front of the robot and send it to PC for processing and extracting useful informations. Together with up to date technologies like SLAM (simultaneous localization and mapping), the robot can localize itself in unknown environment and achieve complex tasks. But during tests it is observed that the images transmitted wirelessly to the PC are obscure and distorted, with low frequency, thus in this work, the camera is not used afterwards. However, it is worth to note that if the blimp is supposed to operates completely autonomously in any indoor environments, the camera is probably the best choice to provide environmental information.
After the first trials on the blimp prototype and summary of experiences, it is finally decided to implement a camera capturing system OptiTrack in the testing room to track the robot and obtain its position and orientation measurements. The OptiTrack system uses infrared waves to capture the reflective markers mounted on blimp control board, and solves the pose of the robot at a rate of 100 frames per second, and the precision for position measurement is 1mm [NaturalPoint, 2018]. A schema for OptiTrack system is shown in Figure 2.5. In fact, the camera capturing system cannot be called as a sensor for the robot, the image processing and pose estimation are achieved by the camera system and then the result is sent to the blimp control system. The OptiTrack enhanced blimp control system will be presented in detail later in Chapter 5.
The advantages of using the camera capturing system are that it provides high precision localization result and orientation measurements of the robot,