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Communications and networking experts from the NASA Glenn Research Center designed and implemented an innovative communications infrastructure for a simulated human-robotic planetary mission. The mission, which was executed in the Arizona desert during the first 2 weeks of September 2002, involved a diverse team of researchers from several NASA centers and academic institutions.
NASA has held an annual robotic mining competition for teams of university/college students since 2010. This competition is yearlong, suitable for a senior university engineering capstone project. It encompasses the full project life cycle from ideation of a robot design, through tele-operation of the robot collecting regolith in simulated Mars conditions, to disposal of the robot systems after the competition. A major required element for this competition is a Systems Engineering Paper in which each team describes the systems engineering approaches used on their project. The score for the Systems Engineering Paper contributes 25% towards the team’s score for the competition’s grand prize. The required use of systems engineering on the project by this competition introduces the students to an intense practical application of systems engineering throughout a full project life cycle.
Several simple multivariable controllers such as proportional (P), proportional-derivative (PD), proportional-integral (PI), and proportional-integral-derivative (PID) are investigated and designed for stabilization and regulation of a two-link planar robot. A new multivariable controller is introduced in this article to achieve command matching. The multivariable controllers are designed on the basis of a linearized model of the robot dynamics. Numerous simulation results are presented to evaluate the performance of the multivariable controllers for the two-link planar robot.
DSS-Prototyper is an open-source, realtime 3D virtual environment software that supports design simulation for the new Vision for Space Exploration (VSE). This is a simulation of NASA's proposed Robotic Lunar Exploration Program, second mission (RLEP2). It simulates the Lunar Surface Access Module (LSAM), which is designed to carry up to four astronauts to the lunar surface for durations of a week or longer. This simulation shows the virtual vehicle making approaches and landings on a variety of lunar terrains. The physics of the descent engine thrust vector, production of dust, and the dynamics of the suspension are all modeled in this set of simulations. The RLEP2 simulations are drivable (by keyboard or joystick) virtual rovers with controls for speed and motor torque, and can be articulated into higher or lower centers of gravity (depending on driving hazards) to enable drill placement. Gravity also can be set to lunar, terrestrial, or zero-g. This software has been used to support NASA's Marshall Space Flight Center in simulations of proposed vehicles for robotically exploring the lunar surface for water ice, and could be used to model all other aspects of the VSE from the Ares launch vehicles and Crew Exploration Vehicle (CEV) to the International Space Station (ISS). This simulator may be installed and operated on any Windows PC with an installed 3D graphics card.
Rover Graphical Simulator (RGS) is a package of software that generates images of the motion of a wheeled robotic exploratory vehicle (rover) across terrain that includes obstacles and regions of varying traversability. The simulated rover moves autonomously, utilizing reasoning and decision-making capabilities of a fuzzy-logic navigation strategy to choose its path from an initial to a final state. RGS provides a graphical user interface for control and monitoring of simulations. The numerically simulated motion is represented as discrete steps with a constant time interval between updates. At each simulation step, a dot is placed at the old rover position and a graphical symbol representing the rover is redrawn at the new, updated position. The effect is to leave a trail of dots depicting the path traversed by the rover, the distances between dots being proportional to the local speed. Obstacles and regions of low traversability are depicted as filled circles, with buffer zones around them indicated by enclosing circles. The simulated robot is equipped with onboard sensors that can detect regional terrain traversability and local obstacles out to specified ranges. RGS won the NASA Group Achievement Award in 2002.
Tele-existence aims at a natural and efficient remote control of robots by providing the operator with a real time sensation of presence. It is an advaced type of teleoperation system which enables a human operator at the controls to perform remote manipulation tasks dexterously with the feeling that he or she exists in one of the remote anthropomorphic robots in the remote environment, e.g., in a hostile environment such as those of nuclear radiation, high temperature, and deep space. In order to study the use of the tele-existence system in the artificially constructed environment, the visual tele-existence simulator has been designed, a pseudo-real-time binocular solid model robot simulator has been made, and its feasibility has been experimentally evaluated. An anthropomorphic robot mechanism with an arm having seven degrees of freedom has been designed and developed as a slave robot for feasibility experiments of teleoperation using the tele-existence method. An impedance controlled active display mechanism and a head mounted display have also been designed and developed as the display subsystem for the master. The robot's structural dimensions are set very close to those of humans.
In this paper, we present the development of ROAMS software for real-time simulation of mobile robotic vehicles.
A system was developed for measuring, in real time, the thickness of a sprayable insulation during its application. The system was graphically modelled, off-line, using a state-of-the-art graphics workstation and associated software. This model was to contain a 3D color model of a workcell containing a robot and an air bearing turntable. A communication link was established between the graphics workstations and the robot's controller. Sequences of robot motion generated by the computer simulation are transmitted to the robot for execution.
Various papers on control paradigms and data structures in sensor fusion are presented. The general topics addressed include: decision models and computational methods, sensor modeling and data representation, active sensing strategies, geometric planning and visualization, task-driven sensing, motion analysis, models motivated biology and psychology, decentralized detection and distributed decision, data fusion architectures, robust estimation of shapes and features, application and implementation. Some of the individual subjects considered are: the Firefly experiment on neural networks for distributed sensor data fusion, manifold traversing as a model for learning control of autonomous robots, choice of coordinate systems for multiple sensor fusion, continuous motion using task-directed stereo vision, interactive and cooperative sensing and control for advanced teleoperation, knowledge-based imaging for terrain analysis, physical and digital simulations for IVA robotics.
A Higher-Order Neural Network (HONN) can be designed to be invariant to geometric transformations such as scale, translation, and in-plane rotation. Invariances are built directly into the architecture of a HONN and do not need to be learned. Thus, for 2D object recognition, the network needs to be trained on just one view of each object class, not numerous scaled, translated, and rotated views. Because the 2D object recognition task is a component of the 3D object recognition task, built-in 2D invariance also decreases the size of the training set required for 3D object recognition. We present results for 2D object recognition both in simulation and within a robotic vision experiment and for 3D object recognition in simulation. We also compare our method to other approaches and show that HONNs have distinct advantages for position, scale, and rotation-invariant object recognition. The major drawback of HONNs is that the size of the input field is limited due to the memory required for the large number of interconnections in a fully connected network. We present partial connectivity strategies and a coarse-coding technique for overcoming this limitation and increasing the input field to that required by practical object recognition problems.
Robots are playing an increasing role in space exploration and in-space servicing. Robotic arms are good for performing in-space tasks such as modular assembly. The SPIDER arm (SPace Infrastructure Dexterous Robot) of the OSAM-1 mission represents an example of a system that can perform modular antenna assembly tasks in environmental conditions that would be dangerous for astronauts. One of the WVRTC activities is to perform independent verification and validation of the SPIDER assembly operations. Space robotic systems adopting large manipulators such as the SPIDER arm are complex to test and verify under normal 1-G conditions. Our work involves proof-of-principle testing of a hardware-inthe-loop (HIL) simulator operating in 1-g conditions, which replicates the motion of the space robot end-effector under the same geometric, kinematic and dynamic conditions, and in response to externally applied forces from its space environment. In particular, our software simulates in real-time the robot dynamics inclusive of flexibility, an important aspect in case of a long robotic arms operating in 0-G conditions. For example, the same oscillatory motions of the space manipulator’s end-effector can be mimicked on ground through our industrial manipulator, allowing us to test the feasibility of complex operation such as assembling modular components.
Various papers on intelligent control and adaptive systems are presented. Individual topics addressed include: control architecture for a Mars walking vehicle, representation for error detection and recovery in robot task plans, real-time operating system for robots, execution monitoring of a mobile robot system, statistical mechanics models for motion and force planning, global kinematics for manipulator planning and control, exploration of unknown mechanical assemblies through manipulation, low-level representations for robot vision, harmonic functions for robot path construction, simulation of dual behavior of an autonomous system. Also discussed are: control framework for hand-arm coordination, neural network approach to multivehicle navigation, electronic neural networks for global optimization, neural network for L1 norm linear regression, planning for assembly with robot hands, neural networks in dynamical systems, control design with iterative learning, improved fuzzy process control of spacecraft autonomous rendezvous using a genetic algorithm.
The NASA Glenn Research Center and academic partners are developing advanced multiagent robotic control algorithms that will enable the autonomous inspection and repair of future propulsion systems. In this application, on-wing engine inspections will be performed autonomously by large groups of cooperative miniature robots that will traverse the surfaces of engine components to search for damage. The eventual goal is to replace manual engine inspections that require expensive and time-consuming full engine teardowns and allow the early detection of problems that would otherwise result in catastrophic component failures. As a preliminary step toward the long-term realization of a practical working system, researchers are developing the technology to implement a proof-of-concept testbed demonstration. In a multiagent system, the individual agents are generally programmed with relatively simple controllers that define a limited set of behaviors. However, these behaviors are designed in such a way that, through the localized interaction among individual agents and between the agents and the environment, they result in self-organized, emergent group behavior that can solve a given complex problem, such as cooperative inspection. One advantage to the multiagent approach is that it allows for robustness and fault tolerance through redundancy in task handling. In addition, the relatively simple agent controllers demand minimal computational capability, which in turn allows for greater miniaturization of the robotic agents.
Testing in relevant environments is key to exploration mission hardware development. This is true on both the component level (in early development) and system level (in late development stages). During ISRU missions the hardware will interface with the soil (digging, roving, etc) in a vacuum environment. A relevant test environment will therefore involve a vacuum chamber with a controlled, conditioned simulant bed. However, in earth-based granular media, such as lunar soil simulant, gases trapped within the material pore structures and water adsorbed to all particle surfaces will release when exposed to vacuum. Early vacuum testing has shown that this gas release can occur violently, which loosens and weakens the simulant, altering the consolidation state. The Vacuum Facility #13, a mid-size chamber (3.66m tall, 1.5m inner diameter) at the NASA Glenn Research Center has been modified to create a soil mechanics test facility. A 0.64m deep by 0.914m square metric ton bed of lunar simulant was placed under vacuum using a variety of pumping techniques. Both GRC-3 and LHT-3M simulant types have been used. An electric cone penetrometer was used to measure simulant strength properties at vacuum including: cohesion, friction angle, bulk density and shear modulus. Simulant disruptions, caused by off gassing, affected the strength properties, but could be mitigated by reducing pump rate. No disruptions were observed at pressures below 2.5Torr, regardless of the pump rate. However, slow off gassing of the soil lead to long test times, a full week, to reach 10-5Torr. This work highlights the need for robotic machine-simulant hardware and operations in vacuum to expeditiously perform (sub-)systems tests.
Robotic manipulators are difficult to program even without the special requirements of a zero-gravity environment. While attention should be paid to investigating the usefulness of industrial application programming methods to space manipulators, new methods with potential application to both environments need to be invented. These methods should allow various levels of autonomy and human-in-the-loop interaction and simple, rapid switching among them. For all methods simulation must be integrated to provide reliability and safety. Graphical programming of manipulators is a candidate for an effective robot programming method despite current limitations in input devices and displays. A research project in task-level robot programming has built an innovative interface to a state-of-the-art commercial simulation and robot programming platform. The prototype demonstrates simple augmented methods for graphical programming and simulation which may be of particular interest to those concerned with Space Station applications; its development has also raised important issues for the development of more sophisticated robot programming tools. Both aspects of the project are discussed.
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.
NASA Ames Research Center is developing a compliant modular tensegrity robotic platform for planetary exploration. In this paper we present the design and evolution of the platform's main hardware component, an untethered, robust tensegrity strut, with rich sensor feedback and cable actuation. Each strut is a complete robot, and multiple struts can be combined together to form a wide range of complex tensegrity robots. Our current goal for the tensegrity robotic platform is the development of SUPERball, a 6-strut icosahedron underactuated tensegrity robot aimed at dynamic locomotion for planetary exploration rovers and landers, but the aim is for the modular strut to enable a wide range of tensegrity morphologies. SUPERball is a second generation prototype, evolving from the tensegrity robot ReCTeR, which is also a modular, lightweight, highly compliant 6-strut tensegrity robot that was used to validate our physics based NASA Tensegrity Robot Toolkit (NTRT) simulator. Many hardware design parameters of the SUPERball were driven by locomotion results obtained in our validated simulator. These evolutionary explorations helped constrain motor torque and speed parameters, along with strut and string stress. As construction of the hardware has finalized, we have also used the same evolutionary framework to evolve controllers that respect the built hardware parameters.
The design and construction of the University of Maryland walking machine was completed during the 1989 to 1990 academic year. It was required that the machine be capable of completing a number of tasks including walking a straight line, turning to change direction, and manuevering over an obstacle such as a set of stairs. The machine consists of two sets of four telescoping legs that alternately support the entire structure. A gear box and crank arm assembly is connected to the leg sets to provide the power required for the translational motion of the machine. By retracting all eight legs, the robot comes to rest on a central Bigfoot support. Turning is accomplished by rotating this machine about this support. The machine can be controlled by using either a user-operated remote tether or the onboard computer for the execution of control commands. Absolute encoders are attached to all motors to provide the control computer with information regarding the status of the motors. Long and short range infrared sensors provide the computer with feedback information regarding the machine's position relative to a series of stripes and reflectors. These infrared sensors simulate how the robot might sense and gain information about the environment of Mars.