Building safer robots: Safety driven control

In recent years there has been a concerted effort to address many of the safety issues associated with physical human-robot interaction (pHRI). However, a number of challenges remain. For personal robots, and those intended to operate in unstructured environments, the problem of safety is compounded. In this paper we argue that traditional system design techniques fail to capture the complexities associated with dynamic environments. We present an overview of our safety-driven control system and its implementation methodology. The methodology builds on traditional functional hazard analysis, with the addition of processes aimed at improving the safety of autonomous personal robots. This will be achieved with the use of a safety system developed during the hazard analysis stage. This safety system, called the safety protection system, will initially be used to verify that safety constraints, identified during hazard analysis, have been implemented appropriately. Subsequently it will serve as a high-level safety enforcer, by governing the actions of the robot and preventing the control layer from performing unsafe operations. To demonstrate the effectiveness of the design, a series of experiments have been conducted using a MobileRobots PeopleBot. Finally, results are presented demonstrating how faults injected into a controller can be consistently identified and handled by the safety protection system. © The Author(s) 2012

Self-Healing Control Framework Against Actuator Fault of Single-Rotor Unmanned Helicopters

Unmanned helicopters (UHs) develop quickly because of their ability to hover and low speed flight. Facing different work conditions, UHs require the ability to safely operate under both external environment constraints, such as obstacles, and their own dynamic limits, especially after faults occurrence. To guarantee the postfault UH system safety and maximum ability, a self‐healing control (SHC) framework is presented in this chapter which is composed of fault detection and diagnosis (FDD), fault‐tolerant control (FTC), trajectory (re‐)planning, and evaluation strategy. More specifically, actuator faults and saturation constraints are considered at the same time. Because of the existence of actuator constraints, usable actuator efficiency would be reduced after actuator fault occurrence. Thus, the performance of the postfault UH system should be evaluated to judge whether the original trajectory and reference is reachable, and the SHC would plan a new trajectory to guarantee the safety of the postfault system under environment constraints. At last, the effectiveness of proposed SHC framework is illustrated by numerical simulations

Advanced flight control system study

A fly by wire flight control system architecture designed for high reliability includes spare sensor and computer elements to permit safe dispatch with failed elements, thereby reducing unscheduled maintenance. A methodology capable of demonstrating that the architecture does achieve the predicted performance characteristics consists of a hierarchy of activities ranging from analytical calculations of system reliability and formal methods of software verification to iron bird testing followed by flight evaluation. Interfacing this architecture to the Lockheed S-3A aircraft for flight test is discussed. This testbed vehicle can be expanded to support flight experiments in advanced aerodynamics, electromechanical actuators, secondary power systems, flight management, new displays, and air traffic control concepts

Classifying intelligence in machines : a taxonomy of intelligent control

The quest to create machines that can solve problems as humans do leads us to intelligent control. This field encompasses control systems that can adapt to changes and learn to improve their actions—traits typically associated with human intelligence. In this work we seek to determine how intelligent these classes of control systems are by quantifying their level of adaptability and learning. First we describe the stages of development towards intelligent control and present a definition based on literature. Based on the key elements of this definition, we propose a novel taxonomy of intelligent control methods, which assesses the extent to which they handle uncertainties in three areas: the environment, the controller, and the goals. This taxonomy is applicable to a variety of robotic and other autonomous systems, which we demonstrate through several examples of intelligent control methods and their classifications. Looking at the spread of classifications based on this taxonomy can help researchers identify where control systems can be made more intelligent

NASA space station automation: AI-based technology review

Research and Development projects in automation for the Space Station are discussed. Artificial Intelligence (AI) based automation technologies are planned to enhance crew safety through reduced need for EVA, increase crew productivity through the reduction of routine operations, increase space station autonomy, and augment space station capability through the use of teleoperation and robotics. AI technology will also be developed for the servicing of satellites at the Space Station, system monitoring and diagnosis, space manufacturing, and the assembly of large space structures

Robusni adaptivni observer temeljen na algoritmu za kooperaciju mobilnih robota s više kotača

Wheeled mobile robots (WMRs) are of great importance. Therefore, it is necessary to make sure that they are not defected. But, in case of failures, the diagnosis task is very important to predict then solve the problem. The most useful techniques in diagnosis are observers which are based on the observability of the monitored system that is not usually ensured by WMR. Thus, to overcome this drawback, an intelligent cooperative diagnosis algorithm is proposed and tested for a group of mobile robots. The diagnosis algorithm is based on robust adaptive unknown input observer applied on unobservable robot. The local non-observability of each robot is solved by cooperative communication. The idea consists on considering all WMRs as a Large Scale System (LSS) even these robots may have not common task. Then, the LSS is decomposed into subsystems that everyone refers to each robot communicating with its neighbors. Next, a design of cooperative interconnected systems is studied to reassure the new condition of observability. Besides, Fast Adaptive Fault Estimation (FAFE) algorithm is proposed to improve the performances of the fault estimation. Finally, to illustrate the efficiency of the proposed algorithm, a model of three-wheel omnidirectional mobile robot is presented.Mobilni roboti na kotačima od velike su važnosti. Stoga, nužno je osigurati da ne odlutaju. U slučaju kvara važna je dijagnoza kako bi se predvidio i onda riješio problem. Najkorisnije dijagnostičke tehnike su observeri koji se zasnivaju na osmotrivosti nadgledanih sustava koja kod mobilnih robota na kotačima najčešće nije osigurana. Stoga, kako bi se nadišao ovaj problem, koristi se inteligentan algoritam za kooperativnu dijagnozu i testira se na grupi mobilnih robota. Dijagnostički algoritam zasniva se na robusnom adaptivnom observeru s nepoznatim ulazom koji je primijenjen na neosmotrivom robotu. Lokalna neosmotrivost svakog robota riješena je koopreativnom komunikacijom. Ideja je da se svi mobilni roboti promatraju kao sustav velikih razmjera iako roboti nemaju isti zadatak. Sustav velikih razmjera se tada rastavlja na podsutave tako da se svaki odnosi na jednog robota koji komunicira sa svojim susjedima. Zatim se proučava dizajn kooperativnih povezanih sustava kako bi se osigurali uvjeti za osmotrivost. Dodatno, predlaže se korištenje brze adaptivne estimacije pogreške kako bi se poboljšala estimacije pogreške. Konačno, prikazan je model višesmjernog mobilnog robota na tri kotača kako bi se ilustrirala učinkovitost predloženog algoritma

Novel approaches for the safety of human-robot interaction

In recent years there has been a concerted effort to address many of the safety issues associated with physical human-robot interaction (pHRI). However, a number of challenges remain. For personal robots, and those intended to operate in unstructured environments, the problem of safety is compounded. We believe that the safety issue is a primary factor in wide scale adoption of personal robots, and until these issues are addressed, commercial enterprises will be unlikely to invest heavily in their development.In this thesis we argue that traditional system design techniques fail to capture the complexities associated with dynamic environments. This is based on a careful analysis of current design processes, which looks at how effectively they identify hazards that may arise in typical environments that a personal robot may be required to operate in. Based on this investigation, we show how the adoption of a hazard check list that highlights particular hazardous areas, can be used to improve current hazard analysis techniques.A novel safety-driven control system architecture is presented, which attempts to address many of the weaknesses identified with the present designs found in the literature. The new architecture design centres around safety, and the concept of a `safety policy' is introduced. These safety policies are shown to be an effective way of describing safety systems as a set of rules that dictate how the system should behave in potentially hazardous situations.A safety analysis methodology is introduced, which integrates both our hazard analysis technique and the implementation of the safety layer of our control system. This methodology builds on traditional functional hazard analysis, with the addition of processes aimed to improve the safety of personal robots. This is achieved with the use of a safety system, developed during the hazard analysis stage. This safety system, called the safety protection system, is initially used to verify that safety constraints, identified during hazard analysis, have been implemented appropriately. Subsequently it serves as a high-level safety enforcer, by governing the actions of the robot and preventing the control layer from performing unsafe operations.To demonstrate the effectiveness of the design, a series of experiments have been conducted using both simulation environments and physical hardware. These experiments demonstrate the effectiveness of the safety-driven control system for performing tasks safely, while maintaining a high level of availability