Autonomous Vertical Autorotation for Unmanned Helicopters

Small Unmanned Aircraft Systems (UAS) are considered the stepping stone for the integration of civil unmanned vehicles in the National Airspace System (NAS) because of their low cost and risk. Such systems are aimed at a variety of applications including search and rescue, surveillance, communications, traffic monitoring and inspection of buildings, power lines and bridges. Amidst these systems, small helicopters play an important role because of their capability to hold a position, to maneuver in tight spaces and to take off and land from virtually anywhere. Nevertheless civil adoption of such systems is minimal, mostly because of regulatory problems that in turn are due to safety concerns. This dissertation examines the risk to safety imposed by UAS in general and small helicopters in particular, focusing on accidents resulting in a ground impact. To improve the performance of small helicopters in this area, the use of autonomous autorotation is proposed. This research goes beyond previous work in the area of autonomous autorotation by developing an on-line, model-based, real-time controller that is capable of handling constraints and different cost functions. The approach selected is based on a non-linear model-predictive controller, that is augmented by a neural network to improve the speed of the non-linear optimization. The immediate benefit of this controller is that a class of failures that would otherwise result in an uncontrolled crash and possible injuries or fatalities can now be accommodated. Furthermore besides simply landing the helicopter, the controller is also capable of minimizing the risk of serious injury to people in the area. This is accomplished by minimizing the kinetic energy during the last phase of the descent. The presented research is designed to benefit the entire UAS community as well as the public, by allowing for safer UAS operations, which in turn also allow faster and less expensive integration of UAS in the NAS

Autonomous Vertical Autorotation for Unmanned Helicopters

Small Unmanned Aircraft Systems (UAS) are considered the stepping stone for the integration of civil unmanned vehicles in the National Airspace System (NAS) because of their low cost and risk. Such systems are aimed at a variety of applications including search and rescue, surveillance, communications, traffic monitoring and inspection of buildings, power lines and bridges. Amidst these systems, small helicopters play an important role because of their capability to hold a position, to maneuver in tight spaces and to take off and land from virtually anywhere. Nevertheless civil adoption of such systems is minimal, mostly because of regulatory problems that in turn are due to safety concerns. This dissertation examines the risk to safety imposed by UAS in general and small helicopters in particular, focusing on accidents resulting in a ground impact. To improve the performance of small helicopters in this area, the use of autonomous autorotation is proposed. This research goes beyond previous work in the area of autonomous autorotation by developing an on-line, model-based, real-time controller that is capable of handling constraints and different cost functions. The approach selected is based on a non-linear model-predictive controller, that is augmented by a neural network to improve the speed of the non-linear optimization. The immediate benefit of this controller is that a class of failures that would otherwise result in an uncontrolled crash and possible injuries or fatalities can now be accommodated. Furthermore besides simply landing the helicopter, the controller is also capable of minimizing the risk of serious injury to people in the area. This is accomplished by minimizing the kinetic energy during the last phase of the descent. The presented research is designed to benefit the entire UAS community as well as the public, by allowing for safer UAS operations, which in turn also allow faster and less expensive integration of UAS in the NAS

uVALVIT: A tool for droplet mobility control and valving

Active control of droplet mobility through low cost tools is highly desirable in applications entailing microfluidics, Lab-on-Chip devices and pertinent technologies. Here, we present the design concepts of a versatile, low cost tool for dynamic droplet mobility manipulation, employing a scheme with backpressure application. Initially sticky open- or closed- channel fluidics with hydrophobic, porous walls are rendered slippery with the application of backpressure through the porous walls. Deliberate control of backpressure directs the wetting phenomena to the desired state. Operation parameters, and control system considerations are presented. Ultra-low backpressure values, are needed for channels with small cross-sections, which in turn are compatible with ultra-low energy demands

On Integrating Unmanned Aircraft Systems into the National Airspace System: Issues, Challenges, Operational Restrictions, Certification, and Recommendations

This book presents, in a comprehensive way, current unmanned aviation regulation, airworthiness certification, special aircraft categories, pilot certification, federal aviation requirements, operation rules, airspace classes and regulation development models. It discusses unmanned aircraft systems levels of safety derived mathematically based on the corresponding levels for manned aviation. It provides an overview of the history and current status of UAS airworthiness and operational regulation worldwide. Existing regulations have been developed considering the need for a complete regulatory framework for UAS. It focuses on UAS safety assessment and functional requirements, achieved in terms of defining an “Equivalent Level of Safety”, or ELOS, with that of manned aviation, specifying what the ELOS requirement entails for UAS regulations. To accomplish this, the safety performance of manned aviation is first evaluated, followed by a novel model to derive reliability requirements for achieving target levels of safety (TLS) for ground impact and mid-air collision accidents.It discusses elements of a viable roadmap leading to UAS integration in to the NAS. For this second edition of the book almost all chapters include major updates and corrections. There is also a new appendix chapter

Adaptive neural network dynamic surface control for musculoskeletal robots

Abstract—Musculoskeletal robots are a class of compliant, tendon-driven robots that can be used in robotics applications, as well as in the study of biological motor systems. Unfor-tunately, there is little progress in controlling such systems. Modern non-linear control approaches are used to overcome the challenges posed by the muscle compliance, the multi-DoF joints, as well as unmodeled dynamic effects such as friction. A controller is derived for a generic model of musculoskeletal robots utilizing a multidimensional form of Dynamic Surface Control (DSC), an extension to backstepping. This controller is extended by an adaptive neural network to compensate for both muscle and joint friction. The developed controllers are evaluated against the state of the art Computed Force Control (CFC), an application of feedback linearization, for a spherical joint which is actuated by five muscles. Keywords—Musculoskeletal robots, dynamic surface control, adaptive neural networks, compliant actuation, non-linear con-trol, backstepping I

Caliper: A universal robot simulation framework for tendon-driven robots

The development of increasingly complex robots in recent years has been characterized by an extensive use of physics-based simulations for controller design and optimization. Today, a variety of open-source and commercial simulators exist for this purpose for mobile and industrial robots. However, existing simulation engines still lack support for the emerging class of tendon-driven robots. In this paper, an innovative simulation framework for the simulation of tendon-driven robots is presented. It consists of a generic physics simulator capable of utilizing CAD robot models and a set of additional tools for simulation control, data acquisition and system investigation. The framework software architecture has been designed using component-based development principles to facilitate the framework extension and customization. Furthermore, for inter-component communication, the operating-system and programming language independent Common Object Request Broker Architecture (CORBA) [1] has been used which simplifies the integration of the framework into existing software environments