Autonomous Fruit Picking With a Team of Aerial Manipulators

Download

Autonomous Fruit Picking with a Team of Aerial Manipulators.pdf

Date

2021-9-7

Author

Köse, Tahsincan

Metadata

Show full item record

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Item Usage Stats

386
views

2946
downloads

Manipulation is the ultimate capability for autonomous micro unmanned aerial vehicles (MAVs), which would enable a substantial number of novel use-cases. Precision agriculture is such a domain with plenty of practical problems that could utilize aerial manipulation, which is faster with respect to ground manipulation. Apple harvesting is the most prominent use case with ever-growing percentages in the overall apple production costs due to increasing imbalance between labor supply and demand. Moreover, contemporary industrial UGVs equipped with arms still strive to compete against human labor financially, which is not the case for relatively cheaper aerial manipulators. Nevertheless, the dynamics of the aerial manipulator is significantly more convoluted when compared to plain quadrotors and thus demand a more sophisticated control pipeline. In this thesis, a brief dynamics analysis on the airframe with a 3 DOF manipulator is conducted and subsequently an appropriate autopilot software with an adequately stable control pipeline -PX4- is selected. Thereafter RRT path planning algorithm family, followed by its multi-robot variant sRRT, which uses subdimensional expansion framework, is introduced. Then the inverse kinematics of 3 DOF arm is introduced, which is used alongside with the local 1 planner in fruit picking. Consecutively a supervised apple detection model based on Mask R-CNN and Data Distillation with real-time capable inference is developed. At the end, multi-robot apple picking scenario is realized and the integration of these submodules is verified in simulation.

Subject Keywords

Robotics, Aerial Manipulation, Precision Agriculture, Fruit Recognition, Multi-robot Path Planning, sRRT, Mask R-CNN

URI

https://hdl.handle.net/11511/93020

Collections

Graduate School of Natural and Applied Sciences, Thesis

Suggestions

OpenMETU
Core

Coordinated guidance for multiple UAVs Cakici, Ferit; Ergezer, Halit; Irmak, Ufuk; Leblebicioğlu, Mehmet Kemal (2016-05-01) This paper addresses the path planning problem of multiple unmanned aerial vehicles (UAVs). The paths are planned to maximize collected amount of information from desired regions (DRs), while avoiding forbidden regions (FRs) and reaching the destination. This study focuses on maximizing collected information instead of minimizing total mission time, as in previous studies. The problem is solved by a genetic algorithm (GA) with the proposal of novel evolutionary operators. The initial populations are generat...
Autonomous quadrotor flight with vision-based obstacle avoidance in virtual environment Eresen, Aydin; Imamoglu, Nevrez; Efe, Mehmet Onder (Elsevier BV, 2012-01-01) In this paper, vision-based autonomous flight with a quadrotor type unmanned aerial vehicle (UAV) is presented. Automatic detection of obstacles and junctions are achieved by the use of optical flow velocities. Variation in the optical flow is used to determine the reference yaw angle. Path to be followed is generated autonomously and the path following process is achieved via a PID controller operating as the low level control scheme. Proposed method is tested in the Google Earth (R) virtual environment fo...
Online path planning for unmanned aerial vehicles to maximize instantaneous information Ergezer, Halit; Leblebicioğlu, Mehmet Kemal (2021-01-01) In this article, an online path planning algorithm for multiple unmanned aerial vehicles (UAVs) has been proposed. The aim is to gather information from target areas (desired regions) while avoiding forbidden regions in a fixed time window starting from the present time. Vehicles should not violate forbidden zones during a mission. Additionally, the significance and reliability of the information collected about a target are assumed to decrease with time. The proposed solution finds each vehicle’s path by s...
Unmanned Aerial Vehicle Domain: Areas of Research Demir, Kadir Alpaslan; Cicibas, Halil; ARICA, NAFİZ (2015-07-01) Unmanned aerial vehicles (UAVs) domain has seen rapid developments in recent years. As the number of UAVs increases and as the missions involving UAVs vary, new research issues surface. An overview of the existing research areas in the UAV domain has been presented including the nature of the work categorised under different groups. These research areas are divided into two main streams: Technological and operational research areas. The research areas in technology are divided into onboard and ground techno...
Biobjective route planning of an unmanned air vehicle in continuous space TEZCANER ÖZTÜRK, DİCLEHAN; Köksalan, Mustafa Murat (2023-02-01) We consider the route planning problem of an unmanned air vehicle (UAV) in a continuous space that is monitored by radars. The UAV visits multiple targets and returns to the base. The routes are constructed considering the total distance traveled and the total radar detection threat objectives. The UAV is capable of moving to any point in the terrain. This leads to infinitely many efficient trajectories between target pairs and infinitely many efficient routes to visit all targets. We use a two stage approa...

Citation Formats

T. Köse, “Autonomous Fruit Picking With a Team of Aerial Manipulators,” M.S. - Master of Science, Middle East Technical University, 2021.