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Testing of ROMPS robot mechanical interfaces and compliant device
The Robot Operated Materials Processing System (ROMPS) has been developed at Goddard Space Flight Center (GSFC) under a flight project to investigate commercially promising in-space material processes and to design reflyable robot automated systems to be used in the above processes for low-cost operations. The ROMPS is currently scheduled for flight in 1994 as a Hitchhiker payload in a Get Away Special (GAS) can. An important component of the ROMPS is a three degree-of-freedom (DOF) robot which will be responsible for carrying out the required tasks of in-space processing of selected materials. This report deals with testing of the mating capability of the ROMPS robot fingers with its various mechanical interfaces. In particular, the test plan will focus on studying the capability of a compliance mechanism mounted on the robot fingers in accommodating misalignments between the robot fingers and the interfaces during the mating. The report is organized as follows: Section 2 represents the main components of the ROMPS robot and briefly describes its operations. Section 3 presents the objectives of the test and outlines the test plan. The testbed comprising a Steward Platform-based high precision manipulator and associated data acquisition and control systems is described in Section 4. Section 5 presents results of numerous experiments conducted to study the mating capability of the robot fingers with its various interfaces under misalignments. The report is concluded with observations and recommendations based on the test results.
Human-Automation Allocations for Current Robotic Space Operations: Space Station Remote Manipulator System
NASA’s Human Research Program’s Risk of Inadequate Design of Human and Automation/Robotic Integration (HARI) delineates the uncertainty surrounding crew work with automation and robotics in spaceflight. HARI is concerned with detrimental effects of ineffective user interfaces, system designs and/or functional task allocation on crew performance, potentially compromising mission success and safety. This risk arises because of limited experience with complex automation and robotics in spaceflight. One key knowledge gap within the HARI risk is related to function allocation.
Enabling Interoperable Space Robots With the Joint Technical Architecture for Robotic Systems (JTARS)
Robots that operate independently of one another will not be adequate to accomplish the future exploration tasks of long-distance autonomous navigation, habitat construction, resource discovery, and material handling. Such activities will require that systems widely share information, plan and divide complex tasks, share common resources, and physically cooperate to manipulate objects. Recognizing the need for interoperable robots to accomplish the new exploration initiative, NASA s Office of Exploration Systems Research & Technology recently funded the development of the Joint Technical Architecture for Robotic Systems (JTARS). JTARS charter is to identify the interface standards necessary to achieve interoperability among space robots. A JTARS working group (JTARS-WG) has been established comprising recognized leaders in the field of space robotics including representatives from seven NASA centers along with academia and private industry. The working group s early accomplishments include addressing key issues required for interoperability, defining which systems are within the project s scope, and framing the JTARS manuals around classes of robotic systems.
A learning controller for nonrepetitive robotic operation
A practical learning control system is described which is applicable to complex robotic and telerobotic systems involving multiple feedback sensors and multiple command variables. In the controller, the learning algorithm is used to learn to reproduce the nonlinear relationship between the sensor outputs and the system command variables over particular regions of the system state space, rather than learning the actuator commands required to perform a specific task. The learned information is used to predict the command signals required to produce desired changes in the sensor outputs. The desired sensor output changes may result from automatic trajectory planning or may be derived from interactive input from a human operator. The learning controller requires no a priori knowledge of the relationships between the sensor outputs and the command variables. The algorithm is well suited for real time implementation, requiring only fixed point addition and logical operations. The results of learning experiments using a General Electric P-5 manipulator interfaced to a VAX-11/730 computer are presented. These experiments involved interactive operator control, via joysticks, of the position and orientation of an object in the field of view of a video camera mounted on the end of the robot arm.
Approach for Autonomous Control of Unmanned Aerial Vehicle Using Intelligent Agents for Knowledge Creation
This paper describes the development of a planned approach for Autonomous operation of an Unmanned Aerial Vehicle (UAV). A Hybrid approach will seek to provide Knowledge Generation through the application of Artificial Intelligence (AI) and Intelligent Agents (IA) for UAV control. The applications of several different types of AI techniques for flight are explored during this research effort. The research concentration is directed to the application of different AI methods within the UAV arena. By evaluating AI and biological system approaches. which include Expert Systems, Neural Networks. Intelligent Agents, Fuzzy Logic, and Complex Adaptive Systems, a new insight may be gained into the benefits of AI and CAS techniques applied to achieving true autonomous operation of these systems. Although flight systems were explored, the benefits should apply to many Unmanned Vehicles such as: Rovers. Ocean Explorers, Robots, and autonomous operation systems. A portion of the flight system is broken down into control agents that represent the intelligent agent approach used in AI. After the completion of a successful approach, a framework for applying an intelligent agent is presented. The initial results from simulation of a security agent for communication are presented.
Analysis of remote operating systems for space-based servicing operations. Volume 2: Study results
The developments in automation and robotics have increased the importance of applications for space based servicing using remotely operated systems. A study on three basic remote operating systems (teleoperation, telepresence and robotics) was performed in two phases. In phase one, requirements development, which consisted of one three-month task, a group of ten missions were selected. These included the servicing of user equipment on the station and the servicing of the station itself. In phase two, concepts development, which consisted of three tasks, overall system concepts were developed for the selected missions. These concepts, which include worksite servicing equipment, a carrier system, and payload handling equipment, were evaluated relative to the configurations of the overall worksite. It is found that the robotic/teleoperator concepts are appropriate for relatively simple structured tasks, while the telepresence/teleoperator concepts are applicable for missions that are complex, unstructured tasks.
Requirements to Design to Code: Towards a Fully Formal Approach to Automatic Code Generation
A general-purpose method to mechanically transform system requirements into a provably equivalent model has yet to appear. Such a method represents a necessary step toward high-dependability system engineering for numerous possible application domains, including distributed software systems, sensor networks, robot operation, complex scripts for spacecraft integration and testing, and autonomous systems. Currently available tools and methods that start with a formal model of a system and mechanically produce a provably equivalent implementation are valuable but not sufficient. The gap that current tools and methods leave unfilled is that their formal models cannot be proven to be equivalent to the system requirements as originated by the customer. For the classes of systems whose behavior can be described as a finite (but significant) set of scenarios, we offer a method for mechanically transforming requirements (expressed in restricted natural language, or in other appropriate graphical notations) into a provably equivalent formal model that can be used as the basis for code generation and other transformations.
Requirements to Design to Code: Towards a Fully Formal Approach to Automatic Code Generation
A general-purpose method to mechanically transform system requirements into a provably equivalent model has yet to appear. Such a method represents a necessary step toward high-dependability system engineering for numerous possible application domains, including distributed software systems, sensor networks, robot operation, complex scripts for spacecraft integration and testing, and autonomous systems. Currently available tools and methods that start with a formal model of a: system and mechanically produce a provably equivalent implementation are valuable but not sufficient. The "gap" that current tools and methods leave unfilled is that their formal models cannot be proven to be equivalent to the system requirements as originated by the customer. For the ciasses of systems whose behavior can be described as a finite (but significant) set of scenarios, we offer a method for mechanically transforming requirements (expressed in restricted natural language, or in other appropriate graphical notations) into a provably equivalent formal model that can be used as the basis for code generation and other transformations.
Autonomous Systems, Robotics, and Computing Systems Capability Roadmap: NRC Dialogue
Contents include the following: Introduction. Process, Mission Drivers, Deliverables, and Interfaces. Autonomy. Crew-Centered and Remote Operations. Integrated Systems Health Management. Autonomous Vehicle Control. Autonomous Process Control. Robotics. Robotics for Solar System Exploration. Robotics for Lunar and Planetary Habitation. Robotics for In-Space Operations. Computing Systems. Conclusion.
Enhanced Lighting Techniques and Augmented Reality to Improve Human Task Performance
One of the most versatile tools designed for use on the International Space Station (ISS) is the Special Purpose Dexterous Manipulator (SPDM) robot. Operators for this system are trained at NASA Johnson Space Center (JSC) using a robotic simulator, the Dexterous Manipulator Trainer (DMT), which performs most SPDM functions under normal static Earth gravitational forces. The SPDM is controlled from a standard Robotic Workstation. A key feature of the SPDM and DMT is the Force/Moment Accommodation (FMA) system, which limits the contact forces and moments acting on the robot components, on its payload, an Orbital Replaceable Unit (ORU), and on the receptacle for the ORU. The FMA system helps to automatically alleviate any binding of the ORU as it is inserted or withdrawn from a receptacle, but it is limited in its correction capability. A successful ORU insertion generally requires that the reference axes of the ORU and receptacle be aligned to within approximately 0.25 inch and 0.5 degree of nominal values. The only guides available for the operator to achieve these alignment tolerances are views from any available video cameras. No special registration markings are provided on the ORU or receptacle, so the operator must use their intrinsic features in the video display to perform the pre-insertion alignment task. Since optimum camera views may not be available, and dynamic orbital lighting conditions may limit viewing periods, long times are anticipated for performing some ORU insertion or extraction operations. This study explored the feasibility of using augmented reality (AR) to assist with SPDM operations. Geometric graphical symbols were overlaid on the end effector (EE) camera view to afford cues to assist the operator in attaining adequate pre-insertion ORU alignment.
NASA's Space Launch System: Positioning Assets for Tele-Robotic Operations
No abstract available
Modeling and Design of an Electro-Rheological Fluid Based Haptic System for Tele-Operation of Space Robots
In this paper a novel haptic interface is presented to enable human-operators to feel and intuitively mirror the stiffness/forces at remote/virtual sites enabling control of robots as human-surrogates.
Real-time collision avoidance in teleoperated whole-sensitive robot arm manipulators
A hybrid robot teleoperation system is presented which makes use of the methodology of motion planning for whole-sensitive robots to assist the operator in generating collision-free motion in a master-slave robot arm manipulator system. The system combines operator commands with data from the sensitive skin to guarantee safe motion for the entire body of the robot arm. The arm avoids obstacles automatically and in real time and moves in a collision-free manner although no prior knowledge of the objects in the environment is available to the motion planning system and no constraints are imposed on the obstacle shapes. The operator is thus relieved of the task of providing safety of the robot arm and surrounding objects.
Design of Space Systems to Enable In-space Assembly and Servicing
For several decades, NASA has employed in-space systems to enhance the performance and extend the useful life of operational orbital assets. In at least one case, an operational mission was not only enhanced, but enabled – the International Space Station was made possible by crewed and robotic in-space assembly, and continues to support installation and operation of new science and technology payloads. In several cases (Hubble Space Telescope, Intelsat 401, Westar and Palapa), major operational assets were rescued or repaired soon after launch when otherwise mission-ending anomalies occurred or were detected. In addition to the original rescue, Hubble was upgraded four times, enabling high-demand, world class science over four decades. More recently, two Northrop Grumman Mission Extension Vehicles have captured two Intelsat spacecraft near the end of their life and fuel capacity, to take over maneuvering duties. In spite of these recent operational achievements, and with the exception of large human exploration vehicles and large space telescopes, space architects rarely consider in-orbit servicing and assembly capabilities in their future planning. Technologies such as multi-launch mission architectures (and rendezvous and proximity operations systems), docking systems, external robotics, advanced tools, modular systems and structures, and fluid transfer systems are available today to support these missions. In-space manufacturing will soon be operational to enable resilient missions that recover from on-orbit failures, and expand the utilization of space. We envision a future that includes these capabilities, and discuss the cultural, engineering, and technological challenges to achieving this vision. We discuss the vision, the proverbial chicken and the egg (which came first, the serviceable spacecraft or the servicer?), the cost, risk, and perceptions thereof of in-space operations, a “spectrum” of cooperative servicing design considerations, and the current status of the space industry’s slow but steady march to widespread operational use of on-orbit servicing, assembly, and manufacturing.
Approach for Autonomous Control of Unmanned Aerial Vehicle Using Intelligent Agents for Knowledge Creation
This paper describes the development of a planned approach for Autonomous operation of an Unmanned Aerial Vehicle (UAV). A Hybrid approach will seek to provide Knowledge Generation thru the application of Artificial Intelligence (AI) and Intelligent Agents (IA) for UAV control. The application of many different types of AI techniques for flight will be explored during this research effort. The research concentration will be directed to the application of different AI methods within the UAV arena. By evaluating AI approaches, which will include Expert Systems, Neural Networks, Intelligent Agents, Fuzzy Logic, and Complex Adaptive Systems, a new insight may be gained into the benefits of AI techniques applied to achieving true autonomous operation of these systems thus providing new intellectual merit to this research field. The major area of discussion will be limited to the UAV. The systems of interest include small aircraft, insects, and miniature aircraft. Although flight systems will be explored, the benefits should apply to many Unmanned Vehicles such as: Rovers, Ocean Explorers, Robots, and autonomous operation systems. The flight system will be broken down into control agents that will represent the intelligent agent approach used in AI. After the completion of a successful approach, a framework of applying a Security Overseer will be added in an attempt to address errors, emergencies, failures, damage, or over dynamic environment. The chosen control problem was the landing phase of UAV operation. The initial results from simulation in FlightGear are presented.
Robotics System Process and Concept for On-orbit Assembly for Potential Mars Sample Return
Proposed Mars Sample Return (MSR) missions would require on-orbit assembly of containment vessels to meet backward Planetary Protection requirements and transfer of the sample container through various stations and positions. Some operations would have to be performed autonomously, and others would require ground-in-loop decision-making stages and verification processes. One concept design for an Earth Return Orbiter (ERO) Capture, Contain, and Return System (CCRS) Transfer Mechanism (TM) is a multi-Degree of Freedom (DOF) manipulator that utilizes a passive End Effector (EE) to assist in containment vessel assembly. To converge on a feasible design, a robotic system process has been instantiated. This process is composed of three main phases: robotic problem definition (operating environment, operations/functions, system goals), robotic solution selection (trade studies on the number of degrees of freedom, number of mechanisms, types of mechanisms), robotic solution design, implementation, and verification and validation (kinematic configuration, robotic and kinematic analysis and topology optimization of components). As a final product of this process, a half-scale functional prototype of the TM was developed to demonstrate the end-to-end operation capability.