Embedded Devices Security Based on ICMetric Technology

An intelligent wheelchair application is required which is equipped with the MEMSs which are magnetometer, gyroscope, and accelerometer sensors. The generated process of ICMetrics number is heavily based on magnetometer, gyroscope, and accelerometer sensors. In addition, this number can be utilised to provide the identification of device. Our proposed system passed through three phases. The first phase is bias reading that was extracted from MEMSs (gyroscope, magnetometer, and accelerometers) sensors; whereas, in the second phase, ICMetric number is generated by using the sensor bias readings that was extracted in the first phase. Therefore, this number is non-stored and can be utilised to provide identification of device. In the third phase, the security system is tested/evaluated to measure its effectivity. In other words, it is tested with dataset that was extracted from the trace file of ns-2. In this phase, performance metrics are calculated, which are rate of error, confused metrics, and accuracy.

Conversion of a Conventional Wheelchair into an Autonomous Personal Transportation Testbed

Personal transportation is the act of transporting an individual by using a small, low-speed vehicle. It is a very hot research topic both in industry and academia. There are many different types of personal transportation vehicles, and wheelchairs are one of them. Autonomous driving is another very popular subject that is applicable to the personal transportation vehicles. Autonomous personal transportation vehicles are good examples of service robotics applications. In this study, conversion procedure of a conventional electric wheelchair into an autonomous personal transportation testbed and the application of some basic autonomous driving algorithms on the developed testbed are explained. In literature, there are several studies providing information on wheelchairs’ autonomy but not deep information about the conversion itself. In this paper, the conversion process is investigated in detail, under two main sections. The first part is by-wire conversion, which allows the wheelchair to be controlled via computer commands. The second part includes the studies on sensors, computational system, and human interface. After making such modifications on wheelchair, fundamental algorithms required for autonomy, such as mapping and localization, are implemented successfully. The results are promising for the usage of the developed system as a testbed for examining new autonomous algorithms and evaluating the performance of the perceptional/computational components.

Safe Human-Robot Interaction Using Variable Stiffness, Hyper-Redundancy, and Smart Robotic Skins

In service robotics, safe human-robot interaction (HRI) is still an open research topic, requiring developments both in hardware and in software as well as their integration. In UMAY1 and MEDICARE-C2projects, we addressed both mechanism design and perception aspects of a framework for safe HRI. Our first focus was to design variable stiffness joints for the robotic neck and arm to enable inherent compliance to protect a human collaborator. We demonstrate the advantages of variable stiffness actuators (VSA) in compliancy, safety, and energy efficiency with applications in exoskeleton and rehabilitation robotics. The variable-stiffness robotic neck mechanism was later scaled down and adopted in the robotic endoscope featuring hyper-redundancy. The hyper-redundant structures are more controllable, having efficient actuation and better feedback. Lastly, a smart robotic skin is introduced to explain the safety support via enhancement of tactile perception. Although it is developed for a hyper-redundant endoscopic robotic platform, the artificial skin can also be integrated in service robotics to provide multimodal tactile feedback. This chapter gives an overview of systems and their integration to attain a safer HRI. We follow a holistic approach for inherent compliancy via mechanism design (i.e., variable stiffness), precise control (i.e., hyper-redundancy), and multimodal tactile perception (i.e., smart robotic-skins).

Development of a Versatile Modular Platform for Aerial Manipulators

The scope of this chapter is the development of an aerial manipulator platform using an octarotor drone with an attached manipulator. An on-board spherical camera provides visual information for the drone’s surroundings, while a Pan-Tilt-Zoom camera system is used to track targets. A powerful computer with a GPU offers significant on-board computational power for the visual servoing of the aerial manipulator system. This vision system, along with the Inertial Management Unit based controller provides exemplary guidance in confined and outdoor spaces. Coupled with the manipulator’s force sensing capabilities the system can interact with the environment. This aerial manipulation system is modular as far as attaching various payloads depending on the application (i.e., environmental sensing, facade cleaning and others, aerial netting for evader-drone geofencing, and others). Experimental studies using a motion capture system are offered to validate the system’s efficiency.

Guidance-Based Motion Planning of Autonomous Systems

Motion planning is a significant stage in the control of autonomous systems. As an alternative method, guidance approach is proposed for the motion planning of those systems. In guided munitions, guidance laws determine the success of the guidance systems designed to steer systems such as missiles and guided bombs towards predefined targets. The guidance laws designated according to determinative agents such as the firing position of the munition, target type, and operational requirements try to provide the munition with arriving at the target point even under the disturbing effects. In this study, the applicability of the guidance laws to autonomous systems is investigated in a manner similar to the approach for the guided munitions. For this purpose, the motion planning of the selected robotic arm, tracked land vehicle, and quadrotor is tried to be performed in order to move them to predefined target points. Having designed the control systems compatible to the selected guidance laws for the considered systems, the corresponding guidance scheme is constructed. Eventually, after conducting the relevant computer simulations, it is observed that the desired target chase can be made in a successive manner for all cases.

Manipulating Complex Robot Behavior for Autonomous and Continuous Operations

Service robot control faces challenges of dynamic environment and complex behavior, which mainly include eye-hand coordination and continuous operations. However, current programming scheme lacks the ability of managing such tasks. In this chapter, we propose a methodology of software development paradigm for the continuous operation of the dual-arm picking robot. First, a dual-arm robot is built for picking with the purpose of selectively harvesting in plant factory. Second, a hierarchical control software is framed by means of “Sense Plan Act” (SPA) paradigm. Third, based on the previous design, programming concept, and the ROS system, the sub-node programming of visual module, motion module, eye-hand coordination module, and task planning module are implemented with a state machine-based architecture. The experimental results show that if total number of targets within the visual field is not more than three, the average picking time is less than 35 s. The fluency of concurrent task management shows the feasibility of manipulating complex robot behavior for autonomous and continuous operations with the finite state machine model and task level architecture.

Application of Artificial Intelligence (AI) in Prosthetic and Orthotic Rehabilitation

Technological integration of Artificial Intelligence (AI) and machine learning in the Prosthetic and Orthotic industry and in the field of assistive technology has become boon for the Persons with Disabilities. The concept of neural network has been used by the leading manufacturers of rehabilitation aids for simulating various anatomical and biomechanical functions of the lost parts of the human body. The involvement of human interaction with various agents’ i.e. electronic circuitry, software, robotics, etc. has made a revolutionary impact in the rehabilitation field to develop devices like Bionic leg, mind or thought control prosthesis and exoskeletons. Application of Artificial Intelligence and robotics technology has a huge impact in achieving independent mobility and enhances the quality of life in Persons with Disabilities (PwDs).

Robotization and Welfare Trends in Future

There are concerns over the present and possible future impact of new advancements like robots and artificial intelligence on welfare. Experts from different fields including science and business have been concentrating on how new developments may affect the job market, and more broadly how new advancements will influence the society. It would be easy to get support for the use of robots for the tasks which are too difficult or too dangerous for humans. What is the capital owners’ focus at that point? What are the economic and social consequences of robotization? In this chapter, literature review including the recent thoughts on how developments in robotics may cause major changes in welfare distribution and revolutionary economic changes is presented.