A Robot Operating System (ROS) based humanoid robot control

This thesis presents adapting techniques required to enhance the capability of a commercially available robot, namely, Robotis Bioloid Premium Humanoid Robot (BPHR). BeagleBone Black (BBB), the decision-making and implementing (intelligence providing) component, with multifunctional capabilities is used in this research. Robot operating System (ROS) and its libraries, as well as Python Script and its libraries have been developed and incorporated into the BBB. This fortified BBB intelligence providing component is then transplanted into the structure of the Robotis Bioloid humanoid robot, after removing the latter’s original decision-making and implementing component (controller). Thus, this study revitalizes the Bioloid humanoid robot by converting it into a humanoid robot with multiple features that can be inherited using ROS. This is a first of its kind approach wherein ROS is used as the development framework in conjunction with the main BBB controller and the software impregnated with Python libraries is used to integrate robotic functions. A full ROS computation is developed and a high level Application Programming Interface (API) usable by software utilizing ROS services is also developed. In this revised two-legged-humanoid robot, USB2Dynamixel connector is used to operate the Dynamixel AX-12A actuators through the Wi-Fi interface of the fortified BBB. An accelerometer sensor supports balancing of the robot, and updates data to the BBB periodically. An Infrared (IR) sensor is used to detect obstacles. This dynamic model is used to actuate the motors mounted on the robot leg thereby resulting in a swing-stance period of the legs for a stable forward movement of the robot. The maximum walking speed of the robot is 0.5 feet/second, beyond this limit the robot becomes unstable. The angle at which the robot leans is governed by the feedback from the accelerometer sensor, which is 20 degrees. If the robot tilts beyond a specific degree, then it would come back to its standstill position and stop further movement. When the robot moves forward, the IR sensors sense obstacles in front of the robot. If an obstacle is detected within 35 cm, then the robot stops moving further. Implementation of ROS on top of the BBB (by replacing CM530 controller with the BBB) and using feedback controls from the accelerometer and IR sensor to control the two-legged robotic movement are the novelties of this work

Project-Based Learning for Robot Control Theory: A Robot Operating System (ROS) Based Approach

Control theory is an important cornerstone of the robotics field and is considered a fundamental subject in an undergraduate and postgraduate robotics curriculum. Furthermore, project-based learning has shown significant benefits in engineering domains, specifically in interdisciplinary fields such as robotics which require hands-on experience to master the discipline adequately. However, designing a project-based learning experience to teach control theory in a hands-on setting can be challenging, due to the rigor of mathematical concepts involved in the subject. Moreover, access to reliable hardware required for a robotics control lab, including the robots, sensors, interfaces, and measurement instruments, may not be feasible in developing countries and even many academic institutions in the US. The current paper presents a set of six project-based assignments for an advanced postgraduate Robot Control course. The assignments leverage the Robot Operating System (ROS), an open-source set of tools, libraries, and software, which is a de facto standard for the development of robotics applications. The use of ROS, along with its physics engine simulation framework, Gazebo, provides a hands-on robotics experience equivalent to working with real hardware. Learning outcomes include: i) theoretical analysis of linear and nonlinear dynamical systems, ii) formulation and implementation of advanced model-based robot control algorithms using classical and modern control theory, and iii) programming and performance evaluation of robotic systems on physics engine robot simulators. Course evaluations and student surveys demonstrate that the proposed project-based assignments successfully bridge the gap between theory and practice, and facilitate learning of control theory concepts and state-of-the-art robotics techniques through a hands-on approach.Comment: 24 pages, 15 figures, accepted for publication in the 2023 ASEE Annual Conference Proceedings, American Society for Engineering Educatio

A Robot Operating System Framework for Secure UAV Communications

To perform advanced operations with unmanned aerial vehicles (UAVs), it is crucial that components other than the existing ones such as flight controller, network devices, and ground control station (GCS) are also used. The inevitable addition of hardware and software to accomplish UAV operations may lead to security vulnerabilities through various vectors. Hence, we propose a security framework in this study to improve the security of an unmanned aerial system (UAS). The proposed framework operates in the robot operating system (ROS) and is designed to focus on sev-eral perspectives, such as overhead arising from additional security elements and security issues essential for flight missions. The UAS is operated in a nonnative and native ROS environment. The performance of the proposed framework in both environments is verified through experiments. © 2021 by the authors. Licensee MDPI, Basel, Switzerland.1

IDF-Autoware: Integrated Development Framework for ROS-Based Self-Driving Systems Using MATLAB/Simulink

This paper proposes an integrated development framework that enables co-simulation and operation of a Robot Operating System (ROS)-based self-driving system using MATLAB/Simulink (IDF-Autoware). The management of self-driving systems is becoming more complex as the development of self-driving technology progresses. One approach to the development of self-driving systems is the use of ROS; however, the system used in the automotive industry is typically designed using MATLAB/Simulink, which can simulate and evaluate the models used for self-driving. These models are incompatible with ROS-based systems. To allow the two to be used in tandem, it is necessary to rewrite the C++ code and incorporate them into the ROS-based system, which makes development inefficient. Therefore, the proposed framework allows models created using MATLAB/Simulink to be used in a ROS-based self-driving system, thereby improving development efficiency. Furthermore, our evaluations of the proposed framework demonstrated its practical potential

People tracking and re-identification by face recognition for RGB-D camera networks

This paper describes a face recognition-based people tracking and re-identification system for RGB-D camera networks. The system tracks people and learns their faces online to keep track of their identities even if they move out from the camera's field of view once. For robust people re-identification, the system exploits the combination of a deep neural network- based face representation and a Bayesian inference-based face classification method. The system also provides a predefined people identification capability: it associates the online learned faces with predefined people face images and names to know the people's whereabouts, thus, allowing a rich human-system interaction. Through experiments, we validate the re-identification and the predefined people identification capabilities of the system and show an example of the integration of the system with a mobile robot. The overall system is built as a Robot Operating System (ROS) module. As a result, it simplifies the integration with the many existing robotic systems and algorithms which use such middleware. The code of this work has been released as open-source in order to provide a baseline for the future publications in this field

Hierarchical task control for aerial inspection

This paper presents a task oriented control strategy for aerial vehicles equipped with a robotic arm and a camera attached to its end-effector. With this setting the camera can reach a new set of orientations previously not feasible for the quadrotor. The over-actuation of the whole system is exploited with a hierarchical control law to achieve a primary task consisting on a visual servoing control, whilst secondary tasks can also be attained to minimize gravitational effects or undesired arm configurations. Results are shown in a Robot Operating System (ROS) simulation.Peer ReviewedPostprint (author’s final draft

Hierarchical task control for aerial inspection

Trabajo presentado al Workshop and Summer School on Field Robotics (euRathlon/ARCAS), celebrado en Sevilla (España) del 15 al 18 de junio de 2014.This paper presents a task oriented control strategy for aerial vehicles equipped with a robotic arm and a camera attached to its end-effector. With this setting the camera can reach a new set of orientations previously not feasible for the quadrotor. The over-actuation of the whole system is exploited with a hierarchical control law to achieve a primary task consisting on a visual servoing control, whilst secondary tasks can also be attained to minimize gravitational effects or undesired arm configurations. Results are shown in a Robot Operating System (ROS) simulation.This work has been partially funded by the EU project ARCAS FP7-287617.Peer Reviewe

DESIGN AND IMPLEMENTATION OF A DISTRIBUTED LEDGER TO SUPPORT DATA SURVIVABILITY IN AN UNMANNED MULTI-VEHICLE SYSTEM

Autonomous vehicle systems, including multi-vehicle systems, are becoming increasingly relevant in military operations. A problem emerges, however, when logging data within these systems. In particular, loss of individual vehicles and inherently lossy and noisy communications environments can result in the loss of important mission data. This thesis presents a novel distributed ledger protocol that can be used to ensure that the data in such a system survives. To test the efficacy of the protocol, we implemented it as a Robot Operating System (ROS) node on the Advanced Robotic Systems Engineering Laboratory (ARSENL) aerial swarm system. Results are presented for implementation tests in the ARSENL software-in-the-loop simulation environment and during live-flight field experiments conducted at Camp Roberts, CA.Outstanding ThesisCivilian, CyberCorps: Scholarship for ServiceApproved for public release. distribution is unlimite