Volume 114 No. 12 2017, 429-436 ISSN: 1311-8080 (printed version); ISSN: 1314-3395 (on-line version) url: http://www.ijpam.eu ijpam.eu INTELLIGENT LANDING TECHNIQUE USING ULTRASONIC SENSOR FOR MAV APPLICATIONS G Sravanthi 1, Shridevi A Mali 2, Siva Subba Rao P 3 1 Madanapalle Institute of Technology & Science, Madanapalle-517325, sravanthi.ece.449@gmail.com 2 GSSS Institute of Engineering & Technology for Women, Mysuru-570016, shrideviamaliec41@gmail.com 3 CSIR-National Aerospace Laboratories, Bengaluru-560017, India, sivapatange@gmail.com Abstract In this paper, ultrasonic sensors are used for the intelligent landing of Micro Arial Vehicle (MAV). An algorithm has been implemented for safe landing on an Arduino Uno microcontroller. The takeoff and landing of MAV is habitually the most significant and accident portion of the mission. Using the developed algorithm the microcontroller gives the distance from MAV to the ground station for safe landing. A flight control board APM 2.6 is connected to the microcontroller board in MAV. The HCSR-04 ultrasonic sensors are connected to the microcontroller board which can detects the distance up to 4m. These ultrasonic sensors are light weight and the detection angle is 30 degree.the ultrasonic sensor used is less complex when compared with other visual(camera) based techniques implemented for safe landing. The processing time in the control loop is faster compared to visual based sensor techniques. So the MAV can land intelligently to the ground using the developed algorithm. It is a cost effect solution and simple method to using in any MAV vehicles. Keywords and Phrases- Ultrasonic sensor, MAV(Micro Aerial Vehicle), Safe Landing System, Distance Measurement 1 INTRODUCTION Micro Aerial Vehicle(MAV) are the drones of small size and does not required any pilot to fly due to their inadequate size. These MAV are the emerging trends in the field of robotics community in the modern years. MAV contains a variety of sensors used for the 429
controlling of the vehicle. Nowadays onboard sensors are implemented on the MAV such as IR sensors, Laser sensors, Stereo cameras. These sensors are required in alternative method for GPS which is suitable for indoor and outdoor environments [7]. In the indoor environment, MAV is used in places like homes and offices for survey, supervision and for entertainment purpose for videography. The safe landing area can be described as a flat surface and without any obstacle to avoid the crash landing. To avoid crash landing an algorithm was developed using ultrasonic sensors, by taking the different parameters obtained from sensors safe landing is performed. The algorithm is computationally efficient and appropriate during fast maneuvers. The quadcopter is used for placing which has four ultrasonic sensors which are controlled by the microcontroller board. 2 RELATED WORK The autonomous landing was first recorded on August 23,1937 in a fixed wing aircraft at Wright Field. In this paper [2], they used onboard receivers were turned on to land unaided MAV. There have been advancements in the technology of compact and robust autopilot landing systems. In this regard HILS simulator was implemented to maintain autonomous take-off [1]. For the safe landing, they took satisfactory results from longitudinal and altitude controls. The existed research Micro Aerial Vehicles(MAVs) depended on the position estimated by the GPS sensors with inertial navigation system data. These type of system works well in higher altitude and in long range, but these are not appropriate for GPS unused environments. 3 ULTRASONIC SENSOR Ultrasonic sound is a type of vibration at a frequency above the range of human hearing of>20 khz. In this experiment, ultrasonic sensor is used to determine the distance of an object from predetermine position. Sensor detection range [5][6] from 0.2m to 4m or 1 to 13 feet. The operation of sensor is not affected by sun light or any black materials like sharp range finders. It has both ultrasonic [4] transmitter and receiver module. The actual picture of sensor shown in figure 3.1 (a). The power supply required is 5V DC with a current 15mA. The resolution of sensor is 0.03m and measuring angle of 30 0. A trigger input pulse of 10μs is to be applied for the initiation of the sensor. The sensor in turn transmits out 8 cycle of ultrasonic burst at 40 KHz and waits for the reflected ultrasonic burst as shown in figure 3.1 (b). When the sensor detects from the receiver it sets the echo pin to high and there is delay for period which is proportional to the distance. Time = Width of the echo pulse(μs), Distance (cm) = Time / 58, Distance (inch)= Time / 148 430
Fig 3.1(a): Ultrasonic sensor (b): Working 8 cycle of 40kHz of the pulse Ultrasonic Sensor 4 BLOCK DIAGRAM OF MAVTRANSMITTER AND RECEIVER OPERATION The MAV has both transmitter and receiver. The microcontroller Arduino board is connected on the MAV. The microcontroller board is interfaced with fourultrasonic sensors. Sensors are positioned on each side of the copter wing to face the ground. Fig 3.1: Block diagram of the MAV system The source code is loaded on microcontroller board using Arduino Integrated Development Environment (IDE) software and which is interfaced with the flight controller board APM 2.6. The APM was connected to sensors like GPS, gyroscope, accelerometer. The servo motors are connected to the board through ESC, which control power to the servo motors. The collected information is transmitted through the channel to the ground station from the telemetry. The baud rate is fixed through the mission plannar software. The mission plannar is free were software which is use to acquire sensor datalogging on through the telemetry. The ground station consists of a telemetry and it receives at the same baud rate. The MAV data is monitored on mission planner software. The mission planner software is calibrated for quadcopter initially. The radio calibration, compass calibration and accelerometer 431
calibrations are performed. Ultrasonic sensor values of distance and voltage is monitored in mission planner software. 5 EXPERMENT SETUP The experimental setup consists of an MAV quadcopter, with all the sensors and control board at 8cm above the ground. The Radio Control (RC) transmitter is used to communicate the flight control board and ground station system. RC transmitter baud rate 57600 is fixed. The servomotors are connected to the power module with the ESC to control the speed of the vehicle. The Arduino board is connected to the flightcontrol board through the telemetry. The trigger and echo pins of the ultrasonic sensors are connected to the Arduino Uno board. Servomotors and propellers Ultrasonic sensors Arduino Uno GPS APM 2.6 ESC Fig 5.1: Front side view and back side view of the setup Battery 6 METHODOLOGY The MAV can be safely landed on the ground by following the steps in the given fig 6.1. The RC transmitter is used to control MAV during the mission. The command from the RC transmitter is given as auto land to the control board present on the MAV vehicle. Ultrasonic sensor obtains the distance from all the sensors placed at different position facing towards the ground. The obtained distances are stored and compared with each sensor distance value. The ultrasonic sensor may show different values of distances obtained by each sensor and are corrected using PID values are adjusted by using manually RC transmitter. After correcting the PID values again sensor distance values are rechecked. If the ultrasonic sensor shows the same distance from each sensor to the ground, then the vehicle is said to be in a stabilised position. The speeds of the servo motors are gradually adjusted. When all sensor distances are 4cmthen the vehicle is in a stabilised position. In case of unequal distances the PID values are again adjusted manually. The altitude and the distance obtained by the ultrasonic sensor are 432
shown on the monitor using mission plannar. The MAV vehicle can be given to auto mode at 350cm as the detection range of the ultrasonic sensor is 400cm. Four sensors are used for landing at an angle of 30 degree to cover overall area. Fig 5.1: Flow Chart of Safe 7 RESULTS AND DISCUSSIONS Landing Satisfactory results were obtained by the algorithm developed. Fig 7.1 shows the graph obtained by the mission plannar and inplot(a) x axis represent ultrasonic sensor distance and y axis represent ultrasonic sensor voltage. The voltage varies with different distance values of ultrasonic sensor. The MAV was connected with the telemetry and that was sending the results to the ground station through the telemetry which is been connected to the mission plannar software. The graph shows that as the distance is increasing the voltage also increases. As the sensor detects up to 4m hence after 4m the voltage attains a constant value. In the fig(b) the graph is obtained to compare the results of altitude sensor and ultrasonic sensor in the safe landing system. The x-axis represents ultrasonic sensor distance measurement and in y-axis the time during flying was considered. It showed a raise in the height of the MAV vehicle and when the command is given to auto land it stabilizes the MAV and it is safely landed by adjusting the PID values. By adjusting the speed of the propeller motor.sssin fig 7.2 the graph is obtained for normal flying of the MAV. The comparison is done with altitude barometric sensor and distance obtained by ultrasonic sensor. In the plotx-axis represents the time taken during flyingand y-axis represents the distance obtained by ultrasonic and altitude sensor. The ultrasonic sensor shows a smooth variation during land compared to the barometric pressure sensor. 433
Fig7.1: a) Variation of voltage with distance, b) Comparison of altitude and ultrasonic sensor in safeland Fig7.2: Comparison of Altitude and Ultrasonic sensor during without safeland 8 CONCLUSION MAV quadcopter was flown with ultrasonic sensor auto landing command is to be given from the RC transmitter. The ultrasonic sensor readings were taken from the mission plannar. The MAV vehicle was automatically landed. The distance of the land was obtained by the ultrasonic sensor then the developed algorithmwas successfully implemented. The plots showed that there was linear increase in the voltage upto 4m later it showed constant voltage for further distances shows sensor gives saturated results. The results were obtained with ultrasonic sensor is comparable with altitude sensor installed in MAV. The plots confirmed that using ultrasonic sensors smooth landing was obtained and developed algorithm makes the MAV land safely. In this experiment a plane land is considered for safe landing and the area not considered as water or any obstacle in line of sight. 434
References [1] Sergio Chiesa, Sara Cresto Aleina, Giovanni Antonio Di Meo, Roberta Fusaro, Autonomous Take-Off And Landing For Unmanned Aircraft System: Risk And Safety Analysis, 29 TH Congress Of The Council Of Aeronautical Sciences. [2] P. Riseborough, Automatic Take-Off and Landing Control for Small UAV s. [3] Pankaj Akuala, Ananda CM Dr Cm, IR and Ultrasonic Sensors Characterization to aid in Atitude estimation during landing of MAV, 3 rd International Conference on Recent Advances in Design, Development and Operation of MAV. [4] Kirtan Gopal Panda, Deepak Agrawal, Arcade Nshimiyimana, Ashraf Hossain, The effects of environment on accuracy of ultrasonic sensor operates in millimetre range, 20 february 2016. [5] Rajan P Thomas, Jithin K K, Hareesh K S, Habeeburahman C A, Jithin Abraham, Range Detection based on Ultrasonic Principle, February 2014. [6] Ultrasonic ranging module HC-SR04 datasheet [online] accessed on 23/08/2016 http://users.ece.utexas.edu/~valvano/datasheets/hcsr04b.pdf [7] Kirillshilov*, The next Generation Design of Autonomous MAV flight control system smartap, department of aeromechanical and flight engineering. [8] Shaowu Yang, Sebastian A. Onboard Monocular Vision for Landing of an MAV on a Landing Site Specified by a Single Reference Image, 2013 International Conference on Unmanned Aircraft Systems (ICUAS) May 28-31, 2013. [9] H. W. Ho, C. De Wagter, B. D. W. Remes, and G. C. H. E. de Croon, Optical-Flow based Self-Supervised Learning of Obstacle Appearance applied to MAV Landing. 435
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