Low-Mass Muscle Actuators Using Electroactive Polymers (EAP)
NASA is seeking to reduce the mass, size, consumed power, and cost of the instrumentation used in its future missions.
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NASA is seeking to reduce the mass, size, consumed power, and cost of the instrumentation used in its future missions.
Perception plays a key role in autonomous and semi-autonomous planetary exploration vehicles. For instance, landers can use computer vision techniques for identifying safe landing locations, aerial vehicles use cameras as navigation sensors, and planetary rovers use them for localization and hazard detection. Engineering simulations of such systems requires the accurate modeling of perception and vision sensors for simulating autonomy scenarios. In addition, the modeling of sensors for landers, aerial and ground vehicles requires the ability to handle large and high-resolution terrains, the accurate modeling of illumination, hi-fidelity rendering via ray/path tracing and the inclusion of sensor characteristics. Vision sensor models strive to simulate sensor reality by using physics principles to model the interaction of light and objects. Furthermore, high frame rate performance is highly desirable for in-the-loop simulations involving vehicle dynamics and control software. In this paper we describe a new sensor modeling capability called Inter-planetary Rendering for Imaging and Sensors (IRIS) that meets these requirements for the real-time and high-fidelity simulation of vision sensors for planetary aerospace and robotics applications.
Provisions for specification of hazards faced by a robotic vehicle (rover) equipped with a rocker-bogie suspension, for prediction of collisions between the vehicle and the hazards, and for simulation of poses of the vehicle at selected positions on the terrain have been incorporated into software that simulates the movements of the vehicle on planned paths across the terrain. The software in question is that of the Web Interface for Telescience (WITS), selected aspects of which have been described in a number of prior NASA Tech Briefs articles. To recapitulate: The WITS is a system of computer software that enables scientists, located at geographically dispersed computer terminals connected to the World Wide Web, to command instrumented robotic vehicles (rovers) during exploration of Mars and perhaps eventually of other planets. The WITS also has potential for adaptation to terrestrial use in telerobotics and other applications that involve computer-based remote monitoring, supervision, control, and planning.
Planetary surfaces are often covered in regolith (crushed rock), whose geologic origin is largely basalt. The lunar surface is made of small-particulate regolith and areas of boulders located in the vicinity of craters. Regolith composition also varies with location, reflecting the local bedrock geology and the nature and efficiency of the micrometeorite-impact processes. In the lowland mare areas (suitable for habitation), the regolith is composed of small granules (20 - 100 microns average size) of mare basalt and volcanic glass. Impacting micrometeorites may cause local melting, and the formation of larger glassy particles, and this regolith may contain 10-80% glass. Studies of lunar regolith are traditionally conducted with lunar regolith simulant (reconstructed soil with compositions patterned after the lunar samples returned by Apollo). The NASA Kennedy Space Center (KSC) Granular Mechanics & Regolith Operations (GMRO) lab has identified a low fidelity but economical geo-technical simulant designated as Black Point-1 (BP-1). It was found at the site of the Arizona Desert Research and Technology Studies (RATS) analog field test site at the Black Point lava flow in adjacent basalt quarry spoil mounds. This paper summarizes activities at KSC regarding the utilization of BP-1 basalt regolith and comparative work with lunar basalt simulant JSC-1A as a building material for robotic additive construction of large structures. In an effort to reduce the import or in-situ fabrication of binder additives, we focused this work on in-situ processing of regolith for construction in a single-step process after its excavation. High-temperature melting of regolith involves techniques used in glassmaking and casting (with melts of lower density and higher viscosity than those of metals), producing basaltic glass with high durability and low abrasive wear. Most Lunar simulants melt at temperatures above 1100 C, although melt processing of terrestrial regolith at 1500 C is not uncommon. These temperatures are achievable by laser heating or by using solar concentrators. Similar to volcanic magma, the cooling rate determines the crystallite size - slower cooling develops larger crystals, and rapid quenching can result in fully amorphous glass.
The National Aeronautics and Space Administration's Reduced Gravity Program (RGP) offers opportunities for experimentation in gravities of less than one-g. The Extravehicular Activity Helper/Retriever (EVAHR) robot project of the Automation and Robotics Division at the Lyndon B. Johnson Space Center in Houston, Texas, is undertaking a task that will culminate in a series of tests in simulated zero-g using this facility. A subset of the final robot hardware consisting of a three-dimensional laser mapper, a Robotics Research 807 arm, a Jameson JH-5 hand, and the appropriate interconnect hardware/software will be used. This equipment will be flown on the RGP's KC-135 aircraft. This aircraft will fly a series of parabolas creating the effect of zero-g. During the periods of zero-g, a number of objects will be released in front of the fixed base robot hardware in both static and dynamic configurations. The system will then inspect the object, determine the objects pose, plan a grasp strategy, and execute the grasp. This must all be accomplished in the approximately 27 seconds of zero-g.
The DOMEX program is a NASA-MMAMA funded project featuring simulations of human crews on Mars focused on science activities that involve collecting samples from the subsurface using both manual and robotic equipment methods and analyzing them in the field and post mission. A crew simulating a human mission to Mars performed activities focused on subsurface science for 2 weeks in November 2009 at Mars Desert Research Station near Hanksville, Utah --an important chemical and morphological Mars analog site. Activities performed included 1) survey of the area to identify geologic provinces, 2) obtaining soil and rock samples from each province and characterizing their mineralogy, chemistry, and biology; 3) site selection and reconnaissance for a future drilling mission; 4) deployment and testing of Mars Underground Mole, a percussive robotic soil sampling device; and 5) recording and analyzing how crew time was used to accomplish these tasks. This paper summarizes results from analysis of soil cores
Supersonic parachutes have been used in nearly every robotic mission to another planetary body with an atmosphere because they are one of the most mass-efficient ways to decelerate a payload to land on the surface. Short of performing flight tests in the upper Earth atmosphere, we currently cannot reliably predict a novel parachute system’s performance or potential failure modes, or even confidently explain it after the fact, as was the case with the Low Density Supersonic Decelerator flight tests and subsequent investigations. Fluid-structure interaction (FSI) simulations have the potential to bridge this gap. To this end, we present several improvements to the state-of-the-art for simulating supersonic parachutes using FSI: a higher effective resolution convective flux, an immersed boundary turbulent wall layer modeling approach to capture viscous effects, and a novel method to obtain a more realistic initial parachute shape. A recent supersonic parachute flight test is simulated and compared to measurements for the purposes of model validation.
This paper argues that an experientally guided robot is necessary to successfully explore far-away planets. Such a robot is characterized as having sense organs which receive sensory information from its environment and motor systems which allow it to interact with that environment. The sensori-motor information which it receives is organized into an experiential knowledge structure and this knowledge in turn is used to guide the robot's future actions. A summary is presented of a problem solving system which is being used as a test bed for developing such a robot. The robot currently engages in the behaviors of visual tracking, focusing down, and looking around in a simulated Martian landscape. Finally, some unsolved problems are outlined whose solutions are necessary before an experientally guided robot can be produced. These problems center around organizing the motivational and memory structure of the robot and understanding its high-level control mechanisms.
Equations are developed to extract the relative joint parameters of an assembled robot arm. Specifically, the Denavit-Hartenberg parameters, which completely characterize the relative joint geometry, are calculated. These parameters are needed to control the hand of the robot arm by resolved rate. As an example, the parameter extraction equations are used with perfect simulated data (no measurement noise) obtained from a mathematical model of a six-degree-of-freedom robot arm. For an actual application, measurement data needed to estimate the relative joint parameters can be generated by moving a robot arm to different positions, measuring the location of the hand (or other extension) in base coordinates, and recording the corresponding joint angles.
With the appearance of general off-the-shelf software packages for the simulation of mechanical systems, modelling and simulation of mechanisms has become an easier task. The authors have recently used one such package, DADS, to model the dynamics of rigid and flexible-link robotic manipulators. In this paper, we present this overview of our learning experiences with DADS, in the hope that it will shorten the learning process for others interested in this software.
A general model of the dynamics of flexible robotic manipulators is presented, including the gross motion of the links, the vibrations of the links and joints, and the dynamic coupling between the gross motions and vibrations. The vibrations in the links may be modeled using lumped parameters, truncated modal summation, a component mode synthesis method, or a mixture of these methods. The local link inertia matrix is derived to obtain the coupling terms between the gross motion of the link and the vibrations of the link. Coupling between the motions of the links results from the kinematic model, which utilizes the method of kinematic influence. The model is used to simulate the dynamics of a flexible space-based robotic manipulator which is attached to a spacecraft, and is free to move with respect to the inertial reference frame. This model may be used to study the dynamic response of the manipulator to the motions of its joints, or to externally applied disturbances.
Autonomous robotic manipulation requires a deep and wide stack of supporting software. This paper presents Autonomous Robotic Manipulator Software (ARMS), a software suite designed at NASA Langley Research Center to support research and development of different algorithms for In-space Servicing, Assembly and Manufacturing (ISAM). ARMS solves common challenges along the autonomous manipulation software stack. Various challenges, such as integration with commercial hardware, simulation, and path planning, are solved through the use of Robot Operating System 2 and its community-developed packages. Other challenges, such as configuration management and task definition, and execution are solved in software built on those tools. The result is a modular approach to robotic system definition, agent actions, and assembly task definitions. ARMS has been used in two ISAM projects at NASA Langley Research Center, the Precision Assembled Space Structures project and the Built On-orbit Robotically assembled Gigatruss project.
Autonomous robotic manipulation requires a deep and wide stack of supporting software. This paper presents Autonomous Robotic Manipulator Software (ARMS), a software suite designed at NASA Langley Research Center to support research and development of different algorithms for In-space Servicing, Assembly and Manufacturing (ISAM). ARMS solves common challenges along the autonomous manipulation software stack. Various challenges, such as integration with commercial hardware, simulation, and path planning, are solved through the use of Robot Operating System 2 and its community-developed packages. Other challenges, such as configuration management and task definition, and execution are solved in software built on those tools. The result is a modular approach to robotic system definition, agent actions, and assembly task definitions. ARMS has been used in two ISAM projects at NASA Langley Research Center, the Precision Assembled Space Structures project and the Built On-orbit Robotically assembled Gigatruss project.
The Laboratory Telerobotic Manipulator (LTM) is a seven-degree-of-freedom robot arm. Two of the arms were delivered to Langley Research Center for ground-based research to assess the use of redundant degree-of-freedom robot arms in space operations. Resolved-rate control equations for the LTM are derived. The equations are based on a scheme developed at the Oak Ridge National Laboratory for computing optimized joint angle rates in real time. The optimized joint angle rates actually represent a trade-off, as the hand moves, between small rates (least-squares solution) and those rates which work toward satisfying a specified performance criterion of joint angles. In singularities where the optimization scheme cannot be applied, alternate control equations are devised. The equations developed were evaluated using a real-time computer simulation to control a 3-D graphics model of the LTM.
Human exploration of Mars will involve both crewed and robotic systems. Many mission concepts involve the deployment and assembly of mission support assets prior to crew arrival on the surface. Some of these deployment and assembly activities will be performed autonomously while others will be performed using teleoperations. However, significant communications latencies between the Earth and Mars make teleoperations challenging. Alternatively, low latency teleoperations are possible from locations in Mars orbit like Mars' moons Phobos and Deimos. To explore these latency opportunities, NASA is conducting a series of studies to investigate the effects of latency on telerobotic deployment and assembly activities. These studies are being conducted in laboratory environments at NASA's Johnson Space Center (JSC), the Human Exploration Research Analog (HERA) at JSC and the NASA Extreme Environment Mission Operations (NEEMO) underwater habitat off the coast of Florida. The studies involve two human-in-the-loop interactive simulations developed by the NASA Exploration Systems Simulations (NExSyS) team at JSC. The first simulation investigates manipulation related activities while the second simulation investigates mobility related activities. The first simulation provides a simple real-time operator interface with displays and controls for a simulated 6 degree of freedom end effector. The initial version of the simulation uses a simple control mode to decouple the robotic kinematic constraints and a communications delay to model latency effects. This provides the basis for early testing with more detailed manipulation simulations planned for the future. Subjects are tested using five operating latencies that represent teleoperation conditions from local surface operations to orbital operations at Phobos, Deimos and ultimately high Martian orbit. Subject performance is measured and correlated with three distance-to-target zones of interest. Each zone represents a target distance ranging from beyond 10m in Zone 1, through 1 cm to contact in Zone 5 with a step size factor of 10. Collected data consists of both objective simulation data (time, distance, hand controller inputs, velocity) and subjective questionnaire data. The second simulation provides a simple real-time operator interface with displays and control of a simulated surface rover. The rover traverses a synthetic Mars-like terrain and must be maneuvered to avoid obstacles while progressing to its destination. Like the manipulator simulation, subjects are tested using five operating latencies that represent teleoperation conditions from local surface operations to orbital operations at Phobos, Deimos and ultimately high Martian orbit. The rover is also operated at three different traverse speeds to assess the correlation between latency and speed. Collected data consisted of both objective simulation data (time, distance, hand controller inputs, braking) and subjective questionnaire data. These studies are exploring relationships between task complexity, operating speeds, operator efficiencies, and communications latencies for low latency teleoperations in support of human planetary exploration. This paper presents early results from these studies along with the current observations and conclusions. These and planned future studies will help to inform NASA on the potential for low latency teleoperations to support human exploration of Mars and inform the design of robotic systems and exploration missions.
sustained and affordable human and robotic program to explore the solar system and beyond. Extend human presence across the solar system, starting with a human return to the Moon by the year 2020, in preparation for human exploration of Mars and other destinations. Develop the innovative technologies, knowledge, and infrastructure both to explore and to support decisions about the destinations for human exploration; and promote international and commercial participation in exploration to further U.S. scientific, security, and economic interests
To continue on a sustainable and flexible path, NASA needs to address the challenge of collecting and moving large amounts of regolith at the destination. NASA’s Regolith Advanced Surface Systems Operations Robot (RASSOR) is principally designed to mine and deliver regolith for In-Situ Resource Utilization (ISRU) processing. RASSOR’s design enables it to efficiently collect and deposit regolith, return collected material for processing, and myriad related ISRU activities. To reliably perform these operations on the lunar surface, RASSOR software and sensory systems need to be robust and maximize the information extracted from a reduced sensor payload. Herein, we present preliminary findings from the Intelligent Capabilities Enhanced RASSOR project. We created reduced-order simulation environments to develop autonomous trenching controllers via reinforcement learning and prototype state estimation architectures. The goal of reinforcement learning is for an agent to learn a policy (task strategy) through interactions with an environment. When the agent performs an action, a change occurs in environment state and a numerical reward is received which informs the agent whether the action performed was good or not. Since reinforcement learning algorithms learn through trial-and-error, a simulation is a desirable first environment for development and learning. We developed two simulations, the first is a 2D excavation simulation developed to facilitate parameter selection, and a 3D simulation developed using a game physics engine, to simulate simplified soil interactions and increase the fidelity of the dynamic models of the robotic agents. The development of this 3D simulation has enabled the training of additional sensing capabilities and research both at the granular mechanics and operations levels. We experimented with various virtual sensor payloads to identify a combination that enabled efficient excavation operation and learning. Our reward function is based on how much material is excavated per step. A penalty is also received for leaving the dig site and to smooth the acceleration of the drum arms. We implemented pseudo time-of-flight sensors to report distance from each drum to ground and the height above ground which was found to be more efficient than existing solutions. Our findings suggest that reinforcement learning for autonomous operations has learned viable trenching strategies within 3000 training episodes in our simplified 2D environment and helped identify desirable sensing capabilities, arrangements, and considerations such as the positioning of time-of-flight sensors. Future work includes expanding our simulation to more complex environments and scenarios, and transfer learning from simulation to RASSOR 2.0 hardware for deployment in the Regolith Test Bin at NASA's Kennedy Space Center.
To manipulate large payloads typical of space construction, the concept of a small arm mounted on the end of a large arm is introduced. The main purposes of such a configuration are to increase the structural stiffness of the robot by bracing against or locking to a stationary frame, and to maintain a firm position constraint between the robot's base and workpieces by grasping them. Possible topologies for a combination of disparate large and small arms are discussed, and kinematics, dynamics, controls, and coordination of the two arms, especially when they brace at the tip of the small arm, are developed. The feasibility and improvement in performance are verified, not only with analytical work and simulation results but also with experiments on the existing arrangement Robotic Arm Large and Flexible and Small Articulated Manipulator.