Underwater Environment SDAP Method Using Multi Single-Beam Sonars

A new autopilot system for unmanned underwater vehicle (UUV) using multi-single-beam sonars is proposed for environmental exploration. The proposed autopilot system is known as simultaneous detection and patrolling (SDAP), which addresses two fundamental challenges: autonomous guidance and control. Autonomous guidance, autonomous path planning, and target tracking are based on the desired reference path which is reconstructed from the sonar data collected from the environmental contour with the predefined safety distance. The reference path is first estimated by using a support vector clustering inertia method and then refined by Bézier curves in order to satisfy the inertia property of the UUV. Differential geometry feedback linearization method is used to guide the vehicle entering into the predefined path while finite predictive stable inversion control algorithm is employed for autonomous target approaching. The experimental results from sea trials have demonstrated that the proposed system can provide satisfactory performance implying its great potential for future underwater exploration tasks

Advanced Line-Follower Robot

In this research, an Advanced Line-follower Robot (ALFR) was designed and built. The ALFR mainly consists of the sensor array (QTR-8A), the high-performance microchips (TMS320f28335, TMS320f28069) and two motors (BLY172S-24V-4000). The ALFR keeps the basic function of the Line-follower Robot (LFR) but applies more advanced control theories, such as Proportional Integral Derivative (PID), Active Disturbance Rejection Control (ADRC) and Iterative Learning Control (ILC). PID and ADRC have been tested in the ALFR. The ALFR control problems and the results have been discussed in this thesis. Suggestions are also provided for research on unsolved problems. In particular, the mathematical models of ALFR have been established for both position and speed control. The solutions based on PID, ADRC and ILC are proposed and tested in simulation. The main objective of this thesis is realized in combining methods from control theories with realities in the context of formulating and solving practical problems in a physical process

Commissioning and System Integration Tests for an Industrial Manipulator Workstation

Industrial systems are composed of several sub systems and architectures that are provided by different manufacturers. System integration aims at enabling a developer to combine these unit systems with limited functionality into one system that can accomplish the execution of required process. Modern integrated systems are developed on top of service-oriented architecture and use webservices for information exchange. Such systems are swiftly deployable and ensure platform interoperability, system adaptability and service reusability. Meanwhile, system integration tests help to reduce the complexity during the integration phase thus ensuring process uniformity. This thesis focuses on deploying a robotic manipulator in an industrial cell. The robot is in-stalled in the assembly line as service provider while services are invoked by using RESTful web services. Second objective of the thesis is to implement a free shape path planning algorithm for the deployed autonomous manipulator to follow the desired curve. The last component of this thesis is focused on developing integration tests to examine and verify the designed system. The robot was commissioned at the FASTory assembly line, installed at FAST lab of Tampere University. The free shape paths were implemented by interpolating Bezier curves using De Casteljau algorithm. System was successfully integrated and verified using Top-down depth first and bottom-up breadth first integration testing approaches