NASA Autonomous Systems & Robotics: Roadmap and Investments
Introduction to NASA STMD approach to autonomous systems and robotics technology development
space robotics↗
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Miniaturized Autonomous Extravehicular Robotic Camera (Mini AERCam)
The NASA Johnson Space Center (JSC) Engineering Directorate is developing the Autonomous Extravehicular Robotic Camera (AERCam), a low-volume, low-mass free-flying camera system . AERCam project team personnel recently initiated development of a miniaturized version of AERCam known as Mini AERCam. The Mini AERCam target design is a spherical "nanosatellite" free-flyer 7.5 inches in diameter and weighing 1 0 pounds. Mini AERCam is building on the success of the AERCam Sprint STS-87 flight experiment by adding new on-board sensing and processing capabilities while simultaneously reducing volume by 80%. Achieving enhanced capability in a smaller package depends on applying miniaturization technology across virtually all subsystems. Technology innovations being incorporated include micro electromechanical system (MEMS) gyros, "camera-on-a-chip" CMOS imagers, rechargeable xenon gas propulsion system , rechargeable lithium ion battery, custom avionics based on the PowerPC 740 microprocessor, GPS relative navigation, digital radio frequency communications and tracking, micropatch antennas, digital instrumentation, and dense mechanical packaging. The Mini AERCam free-flyer will initially be integrated into an approximate flight-like configuration for demonstration on an airbearing table. A pilot-in-the-loop and hardware-in-the-loop simulation to simulate on-orbit navigation and dynamics will complement the airbearing table demonstration. The Mini AERCam lab demonstration is intended to form the basis for future development of an AERCam flight system that provides beneficial on-orbit views unobtainable from fixed cameras, cameras on robotic manipulators, or cameras carried by EVA crewmembers.
Fredrickson, Steven E.↗
SOLL-E: A Module Transport and Placement Robot for Autonomous Assembly of Discrete Lattice Structures
This paper presents the design and development of a transport and placement robot that demonstrates autonomous assembly of structural building blocks. The robots are intended to serve as a critical component of automated structural assembly and maintenance systems. The Scaling Omni-directional Lattice Locomoting Explorer (SOLL-E) uses a 5-DoF bipedal inchworm locomotion architecture with locking foot and cargo grippers. The locomotion system employs large magnet gap diameter BLDC motors with moderate timing belt gearing for primary joints, and DC planetary gearmotors for turning. Foot and cargo grippers are identical, with servo-actuated locking mechanisms. Three modular controller boards are used to control these actuators in real-time, with command and telemetry data transferred between the server and each controller board via WiFi. Functionality and performance were evaluated in a ground demonstration.
robotics↗
Control Architecture for Robotic Agent Command and Sensing
Control Architecture for Robotic Agent Command and Sensing (CARACaS) is a recent product of a continuing effort to develop architectures for controlling either a single autonomous robotic vehicle or multiple cooperating but otherwise autonomous robotic vehicles. CARACaS is potentially applicable to diverse robotic systems that could include aircraft, spacecraft, ground vehicles, surface water vessels, and/or underwater vessels. CARACaS incudes an integral combination of three coupled agents: a dynamic planning engine, a behavior engine, and a perception engine. The perception and dynamic planning en - gines are also coupled with a memory in the form of a world model. CARACaS is intended to satisfy the need for two major capabilities essential for proper functioning of an autonomous robotic system: a capability for deterministic reaction to unanticipated occurrences and a capability for re-planning in the face of changing goals, conditions, or resources. The behavior engine incorporates the multi-agent control architecture, called CAMPOUT, described in An Architecture for Controlling Multiple Robots (NPO-30345), NASA Tech Briefs, Vol. 28, No. 11 (November 2004), page 65. CAMPOUT is used to develop behavior-composition and -coordination mechanisms. Real-time process algebra operators are used to compose a behavior network for any given mission scenario. These operators afford a capability for producing a formally correct kernel of behaviors that guarantee predictable performance. By use of a method based on multi-objective decision theory (MODT), recommendations from multiple behaviors are combined to form a set of control actions that represents their consensus. In this approach, all behaviors contribute simultaneously to the control of the robotic system in a cooperative rather than a competitive manner. This approach guarantees a solution that is good enough with respect to resolution of complex, possibly conflicting goals within the constraints of the mission to be accomplished by the vehicle(s).
Huntsberger, Terrance↗
Cooperative Exploration of Rough Martian Terrains with the "Scorpion" Legged Robot as an Adjunct to a Rover.
NASA needs autonomous robotic exploration of difficult (rough and/or steep) scientifically interesting Martian terrains. Concepts involving distributed autonomy for cooperative robotic exploration are key to enabling new scientific objectives in robotic missions. We propose to utilize a legged robot as an adjunct scout to a rover for access to difficult - scientifically interesting - terrains (rocky areas, slopes, cliffs). Our final mission scenario involves the Ames rover platform "K9" and Scorpion acting together to explore a steep cliff, with the Scorpion robot rappelling down using the K9 as an anchor as well as mission planner and executive. Cooperation concepts, including wheeled rappelling robots have been proposed before. Now we propose to test the combined advantages of a wheeled vehicle with a legged scout as well as the advantages of merging of high level planning and execution with biologically inspired, behavior based robotics. We propose to use the 8-legged, multifunctional autonomous robot platform Scorpion that is currently capable of: Walking on different terrains (rocks, sand, grass, ...). Perceiving its environment and modifying its behavioral pattern accordingly. These capabilities would be extended to enable the Scorpion to: communicate and cooperate with a partner robot; climb over rocks, rubble piles, and objects with structural features. This will be done in the context of exploration of rough terrains in the neighborhood of the rover, but inaccessible to it, culminating in the added capability of rappelling down a steep cliff for both vertical and horizontal terrain observation.
Colombano, Silvano P.↗
A matrix safety frame approach to robot safety for space applications
The planned use of autonomous robots in space applications has generated many new safety problems. This thesis assesses safety of autonomous robot systems through the structure of a proposed three-dimensional matrix safety frame. By identifying the common points of accidents and fatalities involving terrestrial robots, reviewing terrestrial robot safety standards, and modifying and extending these results to space applications, hazards are identified and their associated risks assessed. Three components of the safeguarding dimension of the matrix safety frame, safeguarding through design and operation for intrinsic safety, and incorporation of add-on safety systems are explained through examples for both terrestrial and space robots. A space robot hazard identification checklist, a qualitative tool for robot systems designers, is developed using the structure imparted by the matrix safety frame. The development of an expert system from the contents of the checklist is discussed.
Montgomery, T. D.↗
A fuzzy logic controller for an autonomous mobile robot
The ability of a mobile robot system to plan and move intelligently in a dynamic system is needed if robots are to be useful in areas other than controlled environments. An example of a use for this system is to control an autonomous mobile robot in a space station, or other isolated area where it is hard or impossible for human life to exist for long periods of time (e.g., Mars). The system would allow the robot to be programmed to carry out the duties normally accomplished by a human being. Some of the duties that could be accomplished include operating instruments, transporting objects, and maintenance of the environment. The main focus of our early work has been on developing a fuzzy controller that takes a path and adapts it to a given environment. The robot only uses information gathered from the sensors, but retains the ability to avoid dynamically placed obstacles near and along the path. Our fuzzy logic controller is based on the following algorithm: (1) determine the desired direction of travel; (2) determine the allowed direction of travel; and (3) combine the desired and allowed directions in order to determine a direciton that is both desired and allowed. The desired direction of travel is determined by projecting ahead to a point along the path that is closer to the goal. This gives a local direction of travel for the robot and helps to avoid obstacles.
Yen, John↗
Autonomous Systems & Robotics
Summary of human-system interaction for future human Mars missions and current STMD investments in autonomous systems and robotics.
human-system interaction↗
Unsupervised Change Detection for Space Habitats Using 3D Point Clouds
This work presents an algorithm for scene change detection from point clouds to enable autonomous robotic caretaking in future space habitats. Autonomous robotic systems will help maintain future deep-space habitats, such as the Gateway space station, which will be uncrewed for extended periods. Existing scene analysis software used on the International Space Station (ISS) relies on manually-labeled images for detecting changes. In contrast, the algorithm presented in this work uses raw, unlabeled point clouds as inputs. The algorithm first applies modified Expectation-Maximization Gaussian Mixture Model (GMM) clustering to two input point clouds. It then performs change detection by comparing the GMMs using the Earth Mover’s Distance. The algorithm is validated quantitatively and qualitatively using a test dataset collected by an Astrobee robot in the NASA Ames Granite Lab comprising single frame depth images taken directly by Astrobee and full-scene reconstructed maps built with RGB-D and pose data from Astrobee. The runtimes of the approach are also analyzed in depth. The source code is publicly released to promote further development.
robotics↗
Design, Development and Testing of the Miniature Autonomous Extravehicular Robotic Camera (Mini AERCam) Guidance, Navigation and Control System
Engineers at NASA Johnson Space Center have designed, developed, and tested a nanosatellite-class free-flyer intended for future external inspection and remote viewing of human spaceflight activities. The technology demonstration system, known as the Miniature Autonomous Extravehicular Robotic Camera (Mini AERCam), has been integrated into the approximate form and function of a flight system. The primary focus has been to develop a system capable of providing external views of the International Space Station. The Mini AERCam system is spherical-shaped and less than eight inches in diameter. It has a full suite of guidance, navigation, and control hardware and software, and is equipped with two digital video cameras and a high resolution still image camera. The vehicle is designed for either remotely piloted operations or supervised autonomous operations. Tests have been performed in both a six degree-of-freedom closed-loop orbital simulation and on an air-bearing table. The Mini AERCam system can also be used as a test platform for evaluating algorithms and relative navigation for autonomous proximity operations and docking around the Space Shuttle Orbiter or the ISS.
Wagenknecht, J.↗
Control Algorithms and Simulated Environment Developed and Tested for Multiagent Robotics for Autonomous Inspection of Propulsion Systems
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.
Wong, Edmond↗
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.
Zornetzer, Steve↗
Development of a semi-autonomous service robot with telerobotic capabilities
The importance to the United States of semi-autonomous systems for application to a large number of manufacturing and service processes is very clear. Two principal reasons emerge as the primary driving forces for development of such systems: enhanced national productivity and operation in environments whch are hazardous to humans. Completely autonomous systems may not currently be economically feasible. However, autonomous systems that operate in a limited operation domain or that are supervised by humans are within the technology capability of this decade and will likely provide reasonable return on investment. The two research and development efforts of autonomy and telerobotics are distinctly different, yet interconnected. The first addresses the communication of an intelligent electronic system with a robot while the second requires human communication and ergonomic consideration. Discussed here are work in robotic control, human/robot team implementation, expert system robot operation, and sensor development by the American Welding Institute, MTS Systems Corporation, and the Colorado School of Mines--Center for Welding Research.
Jones, J. E.↗
Very fast motion planning for highly dexterous-articulated robots
Due to the inherent danger of space exploration, the need for greater use of teleoperated and autonomous robotic systems in space-based applications has long been apparent. Autonomous and semi-autonomous robotic devices have been proposed for carrying out routine functions associated with scientific experiments aboard the shuttle and space station. Finally, research into the use of such devices for planetary exploration continues. To accomplish their assigned tasks, all such autonomous and semi-autonomous devices will require the ability to move themselves through space without hitting themselves or the objects which surround them. In space it is important to execute the necessary motions correctly when they are first attempted because repositioning is expensive in terms of both time and resources (e.g., fuel). Finally, such devices will have to function in a variety of different environments. Given these constraints, a means for fast motion planning to insure the correct movement of robotic devices would be ideal. Unfortunately, motion planning algorithms are rarely used in practice because of their computational complexity. Fast methods have been developed for detecting imminent collisions, but the more general problem of motion planning remains computationally intractable. However, in this paper we show how the use of multicomputers and appropriate parallel algorithms can substantially reduce the time required to synthesize paths for dexterous articulated robots with a large number of joints. We have developed a parallel formulation of the Randomized Path Planner proposed by Barraquand and Latombe. We have shown that our parallel formulation is capable of formulating plans in a few seconds or less on various parallel architectures including: the nCUBE2 multicomputer with up to 1024 processors (nCUBE2 is a registered trademark of the nCUBE corporation), and a network of workstations.
Challou, Daniel J.↗
Modular Robotics for Autonomous In-Space Assembly
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autonomy↗
Site Selection and Deployment Scenarios for Servicing of Deep-Space Observatories
The deep-space environment and relative transportation accessibility of the Weak Stability Boundary (WSB) region connecting the Earth-Moon and Sun-Earth libration points makes the Sun-Earth L2 an attractive operating location for future observatories. A summary is presented of key characteristics of future observatories designed to operate in this region. The ability to service observatories that operate within the region around the Lagrange points may greatly enhance their reliability, lifetime, and scientific return. The range of servicing missions might begin with initial deployment, assembly, test, and checkout. Post-assembly servicing missions might also include maintenance and repair, critical fluids resupply, and instrument upgrades. We define the range of servicing missions that can be performed with extravehicular activity, with teleoperated robots, and with autonomous robots. We then describe deployment scenarios that affect payload design. A trade study is summarized of the benefits and risks of alternative servicing sites, including at the International Space Station, at other low-Earth-orbit locations, at the Earth-Moon L1 location, and on-site at the Sun-Earth L2 location. Required technology trades and development issues for observatory servicing at each site, and with each level of autonomy, are summarized.
Willenberg, Harvey J.↗
Working and Learning with Knowledge in the Lobes of a Humanoid's Mind
Humanoid class robots must have sufficient dexterity to assist people and work in an environment designed for human comfort and productivity. This dexterity, in particular the ability to use tools, requires a cognitive understanding of self and the world that exceeds contemporary robotics. Our hypothesis is that the sense-think-act paradigm that has proven so successful for autonomous robots is missing one or more key elements that will be needed for humanoids to meet their full potential as autonomous human assistants. This key ingredient is knowledge. The presented work includes experiments conducted on the Robonaut system, a NASA and the Defense Advanced research Projects Agency (DARPA) joint project, and includes collaborative efforts with a DARPA Mobile Autonomous Robot Software technical program team of researchers at NASA, MIT, USC, NRL, UMass and Vanderbilt. The paper reports on results in the areas of human-robot interaction (human tracking, gesture recognition, natural language, supervised control), perception (stereo vision, object identification, object pose estimation), autonomous grasping (tactile sensing, grasp reflex, grasp stability) and learning (human instruction, task level sequences, and sensorimotor association).
Ambrose, Robert↗
Crew/Robot Coordinated Planetary EVA Operations at a Lunar Base Analog Site
Under the direction of NASA's Exploration Technology Development Program, robots and space suited subjects from several NASA centers recently completed a very successful demonstration of coordinated activities indicative of base camp operations on the lunar surface. For these activities, NASA chose a site near Meteor Crater, Arizona close to where Apollo Astronauts previously trained. The main scenario demonstrated crew returning from a planetary EVA (extra-vehicular activity) to a temporary base camp and entering a pressurized rover compartment while robots performed tasks in preparation for the next EVA. Scenario tasks included: rover operations under direct human control and autonomous modes, crew ingress and egress activities, autonomous robotic payload removal and stowage operations under both local control and remote control from Houston, and autonomous robotic navigation and inspection. In addition to the main scenario, participants had an opportunity to explore additional robotic operations: hill climbing, maneuvering heaving loads, gathering geo-logical samples, drilling, and tether operations. In this analog environment, the suited subjects and robots experienced high levels of dust, rough terrain, and harsh lighting.
Diftler, M. A.↗