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Monitoring ROS2: From Requirements to Autonomous Robots
Context/Goals - Capture mission requirements in high-level language. - Monitor requirements for robots. At a Glance - Transform requirements into runtime monitors for ROS2: - Requirements elicitation.* - Transform requirements into Temporal Logic formulas.* - Transform Temporal Logic formulas into runtime monitors.* - Generate hard real-time code for monitors.* - Generate ROS2 application directly from requirements.+ *Steps done in prior work. +Steps extended from prior work.
Robot dynamics in reduced gravity environment
Robot dynamics and control will become an important issue for productive platforms in space. Robotic operations will be necessary for both man tended stations and for the efficient performance of routine operations in a manned platform. The current constraints on the use of robotic devices in a microgravity environment appears to be due to safety concerns and an anticipated increase in acceleration levels due to manipulator motion. The robot used for the initial studies was a UMI RTX robot, which was adapted to operate in a materials processing workcell to simulate sample changing in a microgravity environment. The robotic cell was flown several times on the KC-135 aircraft at Ellington Field. The primary objective of the initial flights was to determine operating characteristics of both the robot and the operator in the variable gravity of the KC-135 during parabolic maneuvers. It was demonstrated that the KC-135 aircraft can be used for observing dynamics of robotic manipulators. The difficulties associated with humans performing teleoperation tasks during varying G levels were also observed and can provide insight into some areas in which the use of artificial techniques would provide improved system performance. Additionally a graphic simulation of the workcell was developed on a Silicon Graphics Workstation using the IGRIP simulation language from Deneb Robotics. The simulation is intended to be used for predictive displays of the robot operating on the aircraft. It is also anticipated that this simulation can be useful for off-line programming of tasks in the future.
Plan recognition and generalization in command languages with application to telerobotics
A method for pragmatic inference as a necessary accompaniment to command languages is proposed. The approach taken focuses on the modeling and recognition of the human operator's intent, which relates sequences of domain actions ('plans') to changes in some model of the task environment. The salient feature of this module is that it captures some of the physical and linguistic contextual aspects of an instruction. This provides a basis for generalization and reinterpretation of the instruction in different task environments. The theoretical development is founded on previous work in computational linguistics and some recent models in the theory of action and intention. To illustrate these ideas, an experimental command language to a telerobot is implemented. The program consists of three different components: a robot graphic simulation, the command language itself, and the domain-independent pragmatic inference module. Examples of task instruction processes are provided to demonstrate the benefits of this approach.
Types of verbal interaction with instructable robots
An instructable robot is one that accepts instruction in some natural language such as English and uses that instruction to extend its basic repertoire of actions. Such robots are quite different in conception from autonomously intelligent robots, which provide the impetus for much of the research on inference and planning in artificial intelligence. Examined here are the significant problem areas in the design of robots that learn from vebal instruction. Examples are drawn primarily from our earlier work on instructable robots and recent work on the Robotic Aid for the physically disabled. Natural-language understanding by machines is discussed as well as in the possibilities and limits of verbal instruction. The core problem of verbal instruction, namely, how to achieve specific concrete action in the robot in response to commands that express general intentions, is considered, as are two major challenges to instructability: achieving appropriate real-time behavior in the robot, and extending the robot's language capabilities.
QA4, a language for artificial intelligence.
Introduction of a language for problem solving and specifically robot planning, program verification, and synthesis and theorem proving. This language, called question-answerer 4 (QA4), embodies many features that have been found useful for constructing problem solvers but have to be programmed explicitly by the user of a conventional language. The most important features of QA4 are described, and examples are provided for most of the material introduced. Language features include backtracking, parallel processing, pattern matching, set manipulation, and pattern-triggered function activation. The language is most convenient for use in an interactive way and has extensive trace and edit facilities.
Benchmarks of programming languages for special purposes in the space station
Although Ada is likely to be chosen as the principal programming language for the Space Station, certain needs, such as expert systems and robotics, may be better developed in special languages. The languages, LISP and Prolog, are studied and some benchmarks derived. The mathematical foundations for these languages are reviewed. Likely areas of the space station are sought out where automation and robotics might be applicable. Benchmarks are designed which are functional, mathematical, relational, and expert in nature. The coding will depend on the particular versions of the languages which become available for testing.
Automated Constraint Checking of Spacecraft Command Sequences
Robotic Spacecraft are controlled by onboard sets of commands called.
A software toolbox for robotics
A method for programming cooperating manipulators, which is guided by a geometric description of the task to be performed, is given. For this a suitable language must be used and a method for describing the workplace and the objects in it in geometric terms. A task level command language and its implementation for concurrently driven multiple robot arm is described. The language is suitable for driving a cell in which manipulators, end effectors, and sensors are controlled by their own dedicated processors. These processors can communicate with each other through a communication network. A mechanism for keeping track of the history of the commands already executed allows the command language for the manipulators to be event driven. A frame based world modeling system is utilized to describe the objects in the work environment and any relationships that hold between these objects. This system provides a versatile tool for managing information about the world model. Default actions normally needed are invoked when the data base is updated or accessed. Most of the first level error recovery is also invoked by the database by utilizing the concepts of demons. The package can be utilized to generate task level commands in a problem solver or a planner.
Towards Human-Friendly Efficient Control of Multi-Robot Teams
This paper explores means to increase efficiency in performing tasks with multi-robot teams, in the context of natural Human-Multi-Robot Interfaces (HMRI) for command and control. The motivating scenario is an emergency evacuation by a transport convoy of unmanned ground vehicles (UGVs) that have to traverse, in shortest time, an unknown terrain. In the experiments the operator commands, in minimal time, a group of rovers through a maze. The efficiency of performing such tasks depends on both, the levels of robots' autonomy, and the ability of the operator to command and control the team. The paper extends the classic framework of levels of autonomy (LOA), to levels/hierarchy of autonomy characteristic of Groups (G-LOA), and uses it to determine new strategies for control. An UGVoriented command language (UGVL) is defined, and a mapping is performed from the human-friendly gesture-based HMRI into the UGVL. The UGVL is used to control a team of 3 robots, exploring the efficiency of different G-LOA; specifically, by (a) controlling each robot individually through the maze, (b) controlling a leader and cloning its controls to followers, and (c) controlling the entire group. Not surprisingly, commands at increased G-LOA lead to a faster traverse, yet a number of aspects are worth discussing in this context.
Development of automation and robotics for space via computer graphic simulation methods
A robot simulation system, has been developed to perform automation and robotics system design studies. The system uses a procedure-oriented solid modeling language to produce a model of the robotic mechanism. The simulator generates the kinematics, inverse kinematics, dynamics, control, and real-time graphic simulations needed to evaluate the performance of the model. Simulation examples are presented, including simulation of the Space Station and the design of telerobotics for the Orbital Maneuvering Vehicle.
Mission Simulation Toolkit
The Mission Simulation Toolkit (MST) is a flexible software system for autonomy research. It was developed as part of the Mission Simulation Facility (MSF) project that was started in 2001 to facilitate the development of autonomous planetary robotic missions. Autonomy is a key enabling factor for robotic exploration. There has been a large gap between autonomy software (at the research level), and software that is ready for insertion into near-term space missions. The MST bridges this gap by providing a simulation framework and a suite of tools for supporting research and maturation of autonomy. MST uses a distributed framework based on the High Level Architecture (HLA) standard. A key feature of the MST framework is the ability to plug in new models to replace existing ones with the same services. This enables significant simulation flexibility, particularly the mixing and control of fidelity level. In addition, the MST provides automatic code generation from robot interfaces defined with the Unified Modeling Language (UML), methods for maintaining synchronization across distributed simulation systems, XML-based robot description, and an environment server. Finally, the MSF supports a number of third-party products including dynamic models and terrain databases. Although the communication objects and some of the simulation components that are provided with this toolkit are specifically designed for terrestrial surface rovers, the MST can be applied to any other domain, such as aerial, aquatic, or space.
Evaluation of automated decisionmaking methodologies and development of an integrated robotic system simulation. Volume 1: Study results
A variety of artificial intelligence techniques which could be used with regard to NASA space applications and robotics were evaluated. The techniques studied were decision tree manipulators, problem solvers, rule based systems, logic programming languages, representation language languages, and expert systems. The overall structure of a robotic simulation tool was defined and a framework for that tool developed. Nonlinear and linearized dynamics equations were formulated for n link manipulator configurations. A framework for the robotic simulation was established which uses validated manipulator component models connected according to a user defined configuration.
Event-Driven Modeling and Execution of Robotic Activities and Contingencies in the Europa Lander Mission Concept Using BPMN
TRACE (Traceable Robotic Activity Composer and Executive) is a tool designed to address the model-ing, verification, and execution of planned and con-tingent activities during robotic space missions. These activities can be modeled (i.e., planned) graph-ically in TRACE using the Business Process Model and Notation (BPMN) language. This standardized language is used to model a sequence of robotic ac-tivities tied together by logical constructs, events, and time. TRACE includes verification tools to en-sure feasibility before mission models are executed by TRACE’s executive, which is integrated into the autonomy subsystem via a connector. In this paper, we describe TRACE in detail as it would apply to a conceptual Europa Lander surface mission with planned excavation and sample collection activities, as well as, contingency activities when execution is off-nominal—all highlighting our novel use of BPMN as a lingua franca for the pipeline from mis-sion planning to autonomous execution.
Robot computer problem solving system
The conceptual, experimental, and practical phases of developing a robot computer problem solving system are outlined. Robot intelligence, conversion of the programming language SAIL to run under the THNEX monitor, and the use of the network to run several cooperating jobs at different sites are discussed.
A spatial operator algebra for manipulator modeling and control
A powerful new spatial operator algebra for modeling, control, and trajectory design of manipulators is discussed along with its implementation in the Ada programming language. Applications of this algebra to robotics include an operator representation of the manipulator Jacobian matrix; the robot dynamical equations formulated in terms of the spatial algebra, showing the complete equivalence between the recursive Newton-Euler formulations to robot dynamics; the operator factorization and inversion of the manipulator mass matrix which immediately results in O(N) recursive forward dynamics algorithms; the joint accelerations of a manipulator due to a tip contact force; the recursive computation of the equivalent mass matrix as seen at the tip of a manipulator; and recursive forward dynamics of a closed chain system. Finally, additional applications and current research involving the use of the spatial operator algebra are discussed in general terms.
Robot, computer problem solving system
The TENEX computer system, the ARPA network, and computer language design technology was applied to support the complex system programs. By combining the pragmatic and theoretical aspects of robot development, an approach is created which is grounded in realism, but which also has at its disposal the power that comes from looking at complex problems from an abstract analytical point of view.
Excavator Design Validation
The Excavator Design Validation tool verifies excavator designs by automatically generating control systems and modeling their performance in an accurate simulation of their expected environment. Part of this software design includes interfacing with human operations that can be included in simulation-based studies and validation. This is essential for assessing productivity, versatility, and reliability. This software combines automatic control system generation from CAD (computer-aided design) models, rapid validation of complex mechanism designs, and detailed models of the environment including soil, dust, temperature, remote supervision, and communication latency to create a system of high value. Unique algorithms have been created for controlling and simulating complex robotic mechanisms automatically from just a CAD description. These algorithms are implemented as a commercial cross-platform C++ software toolkit that is configurable using the Extensible Markup Language (XML). The algorithms work with virtually any mobile robotic mechanisms using module descriptions that adhere to the XML standard. In addition, high-fidelity, real-time physics-based simulation algorithms have also been developed that include models of internal forces and the forces produced when a mechanism interacts with the outside world. This capability is combined with an innovative organization for simulation algorithms, new regolith simulation methods, and a unique control and study architecture to make powerful tools with the potential to transform the way NASA verifies and compares excavator designs. Energid's Actin software has been leveraged for this design validation. The architecture includes parametric and Monte Carlo studies tailored for validation of excavator designs and their control by remote human operators. It also includes the ability to interface with third-party software and human-input devices. Two types of simulation models have been adapted: high-fidelity discrete element models and fast analytical models. By using the first to establish parameters for the second, a system has been created that can be executed in real time, or faster than real time, on a desktop PC. This allows Monte Carlo simulations to be performed on a computer platform available to all researchers, and it allows human interaction to be included in a real-time simulation process. Metrics on excavator performance are established that work with the simulation architecture. Both static and dynamic metrics are included.