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NASA NTRS2006

AERCam Autonomy: Intelligent Software Architecture for Robotic Free Flying Nanosatellite Inspection Vehicles

The NASA Johnson Space Center has developed a nanosatellite-class Free Flyer intended for future external inspection and remote viewing of human spacecraft. The Miniature Autonomous Extravehicular Robotic Camera (Mini AERCam) technology demonstration unit has been integrated into the approximate form and function of a flight system. The spherical Mini AERCam Free Flyer is 7.5 inches in diameter and weighs approximately 10 pounds, yet it incorporates significant additional capabilities compared to the 35-pound, 14-inch diameter AERCam Sprint that flew as a Shuttle flight experiment in 1997. Mini AERCam hosts a full suite of miniaturized avionics, instrumentation, communications, navigation, power, propulsion, and imaging subsystems, including digital video cameras and a high resolution still image camera. The vehicle is designed for either remotely piloted operations or supervised autonomous operations, including automatic stationkeeping, point-to-point maneuvering, and waypoint tracking. The Mini AERCam Free Flyer is accompanied by a sophisticated control station for command and control, as well as a docking system for automated deployment, docking, and recharge at a parent spacecraft. Free Flyer functional testing has been conducted successfully on both an airbearing table and in a six-degree-of-freedom closed-loop orbital simulation with avionics hardware in the loop. Mini AERCam aims to provide beneficial on-orbit views that cannot be obtained from fixed cameras, cameras on robotic manipulators, or cameras carried by crewmembers during extravehicular activities (EVA s). On Shuttle or International Space Station (ISS), for example, Mini AERCam could support external robotic operations by supplying orthogonal views to the intravehicular activity (IVA) robotic operator, supply views of EVA operations to IVA and/or ground crews monitoring the EVA, and carry out independent visual inspections of areas of interest around the spacecraft. To enable these future benefits with minimal impact on IVA operators and ground controllers, the Mini AERCam system architecture incorporates intelligent systems attributes that support various autonomous capabilities. 1) A robust command sequencer enables task-level command scripting. Command scripting is employed for operations such as automatic inspection scans over a region of interest, and operator-hands-off automated docking. 2) A system manager built on the same expert-system software as the command sequencer provides detection and smart-response capability for potential system-level anomalies, like loss of communications between the Free Flyer and control station. 3) An AERCam dynamics manager provides nominal and off-nominal management of guidance, navigation, and control (GN&C) functions. It is employed for safe trajectory monitoring, contingency maneuvering, and related roles. This paper will describe these architectural components of Mini AERCam autonomy, as well as the interaction of these elements with a human operator during supervised autonomous control.

Fredrickson, Steven E.↗

NASA NTRS2004

Mini AERCam Inspection Robot for Human Space Missions

The Engineering Directorate of NASA Johnson Space Center has developed a nanosatellite-class free-flyer intended for future external inspection and remote viewing of human spacecraft. The Miniature Autonomous Extravehicular Robotic Camera (Mini AERCam) technology demonstration unit has been integrated into the approximate form and function of a flight system. The spherical Mini AERCam free flyer is 7.5 inches in diameter and weighs approximately 10 pounds, yet it incorporates significant additional capabilities compared to the 35 pound, 14 inch AERCam Sprint that flew as a Shuttle flight experiment in 1997. Mini AERCam hosts a full suite of miniaturized avionics, instrumentation, communications, navigation, imaging, power, and propulsion subsystems, including digital video cameras and a high resolution still image camera. The vehicle is designed for either remotely piloted operations or supervised autonomous operations including automatic stationkeeping and point-to-point maneuvering. Mini AERCam is designed to fulfill the unique requirements and constraints associated with using a free flyer to perform external inspections and remote viewing of human spacecraft operations. This paper describes the application of Mini AERCam for stand-alone spacecraft inspection, as well as for roles on teams of humans and robots conducting future space exploration missions.

Fredrickson, Steven E.↗

NASA NTRS2004

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.

Dufrene, Warren R., Jr.↗

NASA NTRS2013

Introduction to Space Resource Mining

There are vast amounts of resources in the solar system that will be useful to humans in space and possibly on Earth. None of these resources can be exploited without the first necessary step of extra-terrestrial mining. The necessary technologies for tele-robotic and autonomous mining have not matured sufficiently yet. The current state of technology was assessed for terrestrial and extraterrestrial mining and a taxonomy of robotic space mining mechanisms was presented which was based on current existing prototypes. Terrestrial and extra-terrestrial mining methods and technologies are on the cusp of massive changes towards automation and autonomy for economic and safety reasons. It is highly likely that these industries will benefit from mutual cooperation and technology transfer.

Mueller, Robert P.↗

NASA NTRS1990

Situationally Driven Local Navigation for Mobile Robots

For mobile robots to autonomously accommodate dynamically changing navigation tasks in a goal-directed fashion, they must employ navigation plans. Any such plan must provide for the robot's immediate and continuous need for guidance while remaining highly flexible in order to avoid costly computation each time the robot's perception of the world changes. Due to the world's uncertainties, creation and maintenance of navigation plans cannot involve arbitrarily complex processes, as the robot's perception of the world will be in constant flux, requiring modifications to be made quickly if they are to be of any use. This work introduces navigation templates (NaT's) which are building blocks for the construction and maintenance of rough navigation plans which capture the relationship that objects in the world have to the current navigation task. By encoding only the critical relationship between the objects in the world and the navigation task, a NaT-based navigation plan is highly flexible; allowing new constraints to be quickly incorporated into the plan and existing constraints to be updated or deleted from the plan. To satisfy the robot's need for immediate local guidance, the NaT's forming the current navigation plan are passed to a transformation function. The transformation function analyzes the plan with respect to the robot's current location to quickly determine (a few times a second) the locally preferred direction of travel. This dissertation presents NaT's and the transformation function as well as the needed support systems to demonstrate the usefulness of the technique for controlling the actions of a mobile robot operating in an uncertain world.

Slack, Marc Glenn↗

NASA NTRS2009

Adaptive Behavior for Mobile Robots

The term "System for Mobility and Access to Rough Terrain" (SMART) denotes a theoretical framework, a control architecture, and an algorithm that implements the framework and architecture, for enabling a land-mobile robot to adapt to changing conditions. SMART is intended to enable the robot to recognize adverse terrain conditions beyond its optimal operational envelope, and, in response, to intelligently reconfigure itself (e.g., adjust suspension heights or baseline distances between suspension points) or adapt its driving techniques (e.g., engage in a crabbing motion as a switchback technique for ascending steep terrain). Conceived for original application aboard Mars rovers and similar autonomous or semi-autonomous mobile robots used in exploration of remote planets, SMART could also be applied to autonomous terrestrial vehicles to be used for search, rescue, and/or exploration on rough terrain.

Huntsberger, Terrance↗

NASA NTRS1997

Dynamics Questions Associated with the AERCam Sprint Free-Flyer

The International Space Station will require the development of small robotic vehicles for such tasks as external inspection, monitoring of extravehicular activities (EVA's) and station build-up, and providing additional lighting at EVA worksites. The Autonomous EVA Robotic Camera (AERCam) family of free-flyers is currently being developed at NASA Johnson Space Center to perform these functions; the first member of the family is the AERCam Sprint vehicle. Many interesting dynamical questions are associated with the Sprint free-flyer. For instance, the reaction of a vehicle which is nearly spherically symmetric (such as Sprint) to a stuck-on thruster is significantly more complicated than that obtained for an idealized, perfectly spherical, spacecraft model. In particular, the real spacecraft will experience a form of forced nutation, with convergence towards either its major or minor principal axis, depending on both the applied torque and the mass properties of the vehicle. Furthermore, the body-fixed jet force vector may have a significant component along this principal axis, so giving rise to a considerable net linear acceleration of the spacecraft. The large velocity that can result is very important, as it may lead to collision with the nearby Orbiter, and is completely overlooked in the idealized analysis. This report will firstly briefly describe the stuck-on thruster dynamics of the real vehicle, and outline how the small products of inertia of the spacecraft determine the time constants of the motion. Secondly, the dynamical effects of a failed-off jet on the Sprint free-flyer will be described in more detail, and compared with the stuck-on thruster case. This will help to show whether the two malfunctions should be dealt with differently in flight. Finally, the stuck-on thruster detection software (known as the uncommanded motion algorithm) that is proposed to be flown on the Sprint vehicle will be analyzed, and all possible perturbation sources that may tend to give rise to false stuck-on thruster alarms quantified. It will be shown that false alarms can be triggered by discrete events such as a failed-off thruster, a glancing collision with Orbiter structure, or thruster saturation. They can also be triggered by a combination of errors introduced by constantly present sources such as thrust level errors, thruster misalignment, inertial cross-coupling, angular rate sensor noise, and structural vibrations induced by thruster firings. Based on this fact, the original plan to have the spacecraft enter safe mode whenever the uncommanded motion algorithm is triggered does not appear to be advisable. A better approach seems to be to provide the Sprint pilot with a warning whenever uncommanded motion is detected, and then allow the crew to determine whether safing the vehicle is appropriate.

Williams, Trevor↗

NASA NTRS2000

Vision-Guided Autonomous Stair Climbing

The Tactical Mobile Robot (TMR) program calls for autonomous mobility in an urban environment. Among all man-made structures which pose as barriers for a mobile robot, stairs are the most obvious and ubiquitous structure an autonomous urban robot needs to be able to handle.

Mobile↗

NASA NTRSDate not supplied

Astrobee On-Orbit Commissioning Manuscript and Presentation

The Astrobee free flying robots operate autonomously inside the International Space Station (ISS) with oversight from a ground operator or ISS crew. They replace the Synchronized Position Hold Engage and Reorient Experimental Satellites (SPHERES) as research platforms for zero-g free-flying robotics. Astrobee can also serve as a mobile camera/sensor platform for flight and payload controllers to improve ISS operations. Development began in late 2014, and flight hardware deployed to the ISS on several launches starting from November 2018 to October 2019. Shortly after the first two robots arrived in April 2019, we began a series of commissioning activities to validate the Astrobee robots. This paper reviews the Astrobee system and describes the on-orbit commissioning activities and results.

ISS↗

NASA NTRSDate not supplied

Astrobee On-Orbit Commissioning

ISS↗

NASA NTRS1992

Sensor fusion V; Proceedings of the Meeting, Boston, MA, Nov. 15-17, 1992

Topics addressed include 3D object perception, human-machine interface in multisensor systems, sensor fusion architecture, fusion of multiple and distributed sensors, interface and decision models for sensor fusion, computational networks, simple sensing for complex action, multisensor-based control, and metrology and calibration of multisensor systems. Particular attention is given to controlling 3D objects by sketching 2D views, the graphical simulation and animation environment for flexible structure robots, designing robotic systems from sensorimotor modules, cylindrical object reconstruction from a sequence of images, an accurate estimation of surface properties by integrating information using Bayesian networks, an adaptive fusion model for a distributed detection system, multiple concurrent object descriptions in support of autonomous navigation, robot control with multiple sensors and heuristic knowledge, and optical array detectors for image sensors calibration. (No individual items are abstracted in this volume)

Schenker, Paul S.↗

NASA NTRS2019

Towards Resilient Autonomous Navigation of Drones

Robots and particularly drones are especially useful in exploring extreme environments that pose hazards to humans. To ensure safe operations in these situations, usually perceptually degraded and without good GNSS, it is critical to have a reliable and robust state estimation solution. The main body of literature in robot state estimation focuses on developing complex algorithms favoring accuracy. Typically, these approaches rely on a strong underlying assumption: the main estimation engine will not fail during operation. In contrast, we propose an architecture that pursues robustness in state estimation by considering redundancy and heterogeneity in both sensing and estimation algorithms. The architecture is designed to expect and detect failures and adapt the behavior of the system to ensure safety. To this end, we present HeRO (Heterogeneous Redundant Odometry): a stack of estimation algorithms running in parallel supervised by a resiliency logic. This logic carries out three main functions: a) perform confidence tests both in data quality and algorithm health; b) re-initialize those algorithms that might be malfunctioning; c) generate a smooth state estimate by multiplexing the inputs based on their quality. The state and quality estimates are used by the guidance and control modules to adapt the mobility behaviors of the system. The validation and utility of the approach are shown with real experiments on a ying robot for the use case of autonomous exploration of subterranean environments, with particular results from the STIX event of the DARPA Subterranean Challenge.

Agha-mohammadi, Ali-akbar↗

NASA NTRSDate not supplied

The Troupe System: an Autonomous Multi-Agent Rover Swarm

Autonomous cooperative robotic systems are the future of space exploration. The complexity of such systems makes their development, verification and assurance challenging. The Robust Software Engineering group at NASA Ames has developed the Troupe project that aims to explore the design and development of a swarm of autonomous rovers tasked to perform autonomous exploration and mapping of an unknown terrain. In this paper, we showcase the system design, and accompanying verification and validation tools integrated in the Troupe system development life-cycle.

TROUPE↗

NASA NTRS2004

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.

Dufrene, Warren R., Jr.↗

NASA NTRS2004

Mobile Autonomous Humanoid Assistant

A mobile autonomous humanoid robot is assisting human co-workers at the Johnson Space Center with tool handling tasks. This robot combines the upper body of the National Aeronautics and Space Administration (NASA)/Defense Advanced Research Projects Agency (DARPA) Robonaut system with a Segway(TradeMark) Robotic Mobility Platform yielding a dexterous, maneuverable humanoid perfect for aiding human co-workers in a range of environments. This system uses stereo vision to locate human team mates and tools and a navigation system that uses laser range and vision data to follow humans while avoiding obstacles. Tactile sensors provide information to grasping algorithms for efficient tool exchanges. The autonomous architecture utilizes these pre-programmed skills to form human assistant behaviors. The initial behavior demonstrates a robust capability to assist a human by acquiring a tool from a remotely located individual and then following the human in a cluttered environment with the tool for future use.

Diftler, M. A.↗

NASA NTRS2012

Mini AERCam for In-Space Inspection

The NASA Johnson Space Center Engineering Directorate has developed the Miniature Autonomous Extravehicular Robotic Camera (Mini AERCam) as a free-flying, robotic inspection vehicle intended for future external inspection and remote viewing of human spacecraft. The Mini AERCam technology demonstration unit has been successfully integrated into the approximate form and function of a nanosatellite flight system by leveraging the success of AERCam Sprint flight system and related free-flyer technology development. The Mini AERCam free flyer can be operated via remote piloting from a control station supporting teleoperation and supervised autonomous commanding, with functions such as automatic stationkeeping, point-to-point maneuvering, and automatic docking. Free-flyer testing has been conducted on an air-bearing table and in a six degree-of-freedom closed-loop orbital simulation, and enhancements have been made to provide additional capabilities for future space-based inspection. This presentation will provide a technical overview of the Mini AERCam development, including strategies for spacecraft integration.

Fredrickson, Steven E.↗

NASA NTRS2003

Bio-inspired Computing for Robots

Living creatures may provide algorithms to enable active sensing/control systems in robots. Active sensing could enable planetary rovers to feel their way in unknown environments. The surface of Jupiter's moon Europa consists of fractured ice over a liquid sea that may contain microbes similar to those on Earth. To explore such extreme environments, NASA needs robots that autonomously survive, navigate, and gather scientific data. They will be too far away for guidance from Earth. They must sense their environment and control their own movements to avoid obstacles or investigate a science opportunity. To meet this challenge, CICT's Information Technology Strategic Research (ITSR) Project is funding neurobiologists at NASA's Jet Propulsion Laboratory (JPL) and selected universities to search for biologically inspired algorithms that enable robust active sensing and control for exploratory robots. Sources for these algorithms are living creatures, including rats and electric fish.

Laufenberg, Larry↗

NASA NTRS2006

Improving Grasp Skills Using Schema Structured Learning

Abstract In the control-based approach to robotics, complex behavior is created by sequencing and combining control primitives. While it is desirable for the robot to autonomously learn the correct control sequence, searching through the large number of potential solutions can be time consuming. This paper constrains this search to variations of a generalized solution encoded in a framework known as an action schema. A new algorithm, SCHEMA STRUCTURED LEARNING, is proposed that repeatedly executes variations of the generalized solution in search of instantiations that satisfy action schema objectives. This approach is tested in a grasping task where Dexter, the UMass humanoid robot, learns which reaching and grasping controllers maximize the probability of grasp success.

Platt, Robert↗