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At least 361 records · Page 20

Video Guidance Sensor for Surface Mobility Operations

Robotic systems and surface mobility will play an increased role in future exploration missions. Unlike the LRV during Apollo era which was an astronaut piloted vehicle future systems will include teleoperated and semi-autonomous operations. The tasks given to these vehicles will run the range from infrastructure maintenance, ISRU, and construction to name a few. A common task that may be performed would be the retrieval and deployment of trailer mounted equipment. Operational scenarios may require these operations to be performed remotely via a teleoperated mode,or semi-autonomously. This presentation describes the on-going project to adapt the Automated Rendezvous and Capture (AR&C) sensor developed at the Marshall Space Flight Center for use in an automated trailer pick-up and deployment operation. The sensor which has been successfully demonstrated on-orbit has been mounted on an iRobot/John Deere RGATOR autonomous vehicle for this demonstration which will be completed in the March 2008 time-frame.

Fernandez, Kenneth R.↗

International Space Station Crew Restraint Design

With permanent human presence onboard the International Space Station (ISS), crews will be living and working in microgravity, dealing with the challenges of a weightless environment. In addition, the confined nature of the spacecraft environment results in ergonomic challenges such as limited visibility and access to the activity areas, as well as prolonged periods of unnatural postures. Without optimum restraints, crewmembers may be handicapped for performing some of the on-orbit tasks. Currently, many of the tasks on ISS are performed with the crew restrained merely by hooking their arms or toes around handrails to steady themselves. This is adequate for some tasks, but not all. There have been some reports of discomfort/calluses on the top of the toes. In addition, this type of restraint is simply insufficient for tasks that require a large degree of stability. Glovebox design is a good example of a confined workstation concept requiring stability for successful use. They are widely used in industry, university, and government laboratories, as well as in the space environment, and are known to cause postural limitations and visual restrictions. Although there are numerous guidelines pertaining to ventilation, seals, and glove attachment, most of the data have been gathered in a 1-g environment, or are from studies that were conducted prior to the early 1980 s. Little is known about how best to restrain a crewmember using a glovebox in microgravity. In 2004, The Usability Testing and Analysis Facility (UTAF) at the NASA Johnson Space Center completed development/evaluation of several design concepts for crew restraints to meet the various needs outlined above. Restraints were designed for general purpose use, for teleoperation (Robonaut) and for use with the Life Sciences Glovebox. All design efforts followed a human factors engineering design lifecycle, beginning with identification of requirements followed by an iterative prototype/test cycle. Anthropometric modeling was completed for the 5th percentile Asian female and the 95th percentile American male for all restraints. A series of three evaluations was performed onboard NASA's reduced gravity aircraft (KC-135). For all evaluations, participants performed representative tasks while being videotaped, and then completed a questionnaire following each flight day. The questionnaire included ratings scales and free format questions to assess topics such as comfort, stability provided, flexibility provided, etc. Results from the three flight evaluations are being used to develop the human factors design requirements for crew restraint concepts for 1) general purpose restraints, 2) teleoperation restraints and 3) glovebox restraints. The poster presentation will describe the detailed methodology used, results from each of the three evaluations, and the resulting human factors recommendations for the design of these restraints.

Whitmore, M.↗

Space Station Human Factors: Designing a Human-Robot Interface

The experiments described in this paper are part of a larger joint MIT/NASA research effort and focus on the development of a methodology for designing and evaluating integrated interfaces for highly dexterous and multifunctional telerobot. Specifically, a telerobotic workstation is being designed for an Extravehicular Activity (EVA) anthropomorphic space station telerobot called Robonaut. Previous researchers have designed telerobotic workstations based upon performance of discrete subsets of tasks (for example, peg-in-hole, tracking, etc.) without regard for transitions that operators go through between tasks performed sequentially in the context of larger integrated tasks. The experiments presented here took an integrated approach to describing teleoperator performance and assessed how subjects operating a full-immersion telerobot perform during fine position and gross position tasks. In addition, a Robonaut simulation was also developed as part of this research effort, and experimentally tested against Robonaut itself to determine its utility. Results show that subject performance of teleoperated tasks using both Robonaut and the simulation are virtually identical, with no significant difference between the two. These results indicate that the simulation can be utilized as both a Robonaut training tool, and as a powerful design platform for telepresence displays and aids.

Rochlis, Jennifer L.↗

Human-Robot Interaction

Risk of Inadequate Design of Human and Automation/Robotic Integration (HARI) is a new Human Research Program (HRP) risk. HRI is a research area that seeks to understand the complex relationship among variables that affect the way humans and robots work together to accomplish goals. The DRP addresses three major HRI study areas that will provide appropriate information for navigation guidance to a teleoperator of a robot system, and contribute to the closure of currently identified HRP gaps: (1) Overlays -- Use of overlays for teleoperation to augment the information available on the video feed (2) Camera views -- Type and arrangement of camera views for better task performance and awareness of surroundings (3) Command modalities -- Development of gesture and voice command vocabularies

Rochlis-Zumbado, Jennifer↗

Supervisory Control of a Humanoid Robot in Microgravity for Manipulation Tasks

Teleoperation is the dominant form of dexterous robotic tasks in the field. However, there are many use cases in which direct teleoperation is not feasible such as disaster areas with poor communication as posed in the DARPA Robotics Challenge, or robot operations on spacecraft a large distance from Earth with long communication delays. Presented is a solution that combines the Affordance Template Framework for object interaction with TaskForce for supervisory control in order to accomplish high level task objectives with basic autonomous behavior from the robot. TaskForce, is a new commanding infrastructure that allows for optimal development of task execution, clear feedback to the user to aid in off-nominal situations, and the capability to add autonomous verification and corrective actions. This framework has allowed the robot to take corrective actions before requesting assistance from the user. This framework is demonstrated with Robonaut 2 removing a Cargo Transfer Bag from a simulated logistics resupply vehicle for spaceflight using a single operator command. This was executed with 80% success with no human involvement, and 95% success with limited human interaction. This technology sets the stage to do any number of high level tasks using a similar framework, allowing the robot to accomplish tasks with minimal to no human interaction.

Farrell, Logan C.↗

Mass Inferencing Model Creation and Deployment to the RASSOR Lunar Excavation Robot

The Regolith Advanced Surface Systems Operations Robot (RASSOR) Excavator is a teleoperated mobile robotic platform with a unique space regolith excavation capability. The Intelligent Capabilities Enhanced RASSOR research project developed functionality for inferencing regolith mass ingested during RASSOR operation, enhancing RASSOR’s ability to successfully complete ISRU missions. To teleoperate or run autonomously, it is crucial for the quantity of regolith mass ingested by RASSOR to be available as a system state for efficient operation. For example, during autonomous operation, RASSOR should navigate and move to a processing plant to offload the collected regolith when the drums are full; without knowledge of how much mass is in the drums, this type of high-level planning is not possible. Four distinct modeling approaches were employed in developing a mass inferencing approach that could work on RASSOR. All take in system states, such as arm/drum positions, velocities, currents, voltages, and robot pose, and output a mass prediction for each set of the robot’s bucket drums.1) A neural network model that takes a vector of normalized system states; 2) A model that uses the integrated power consumption of an arm-raise (normalized by velocity); 3) A model that uses average drum current over a variable length interval of the drum disengaged from the surface; and 4) A real-time estimation model that aggregates excavation drum current. The developed models run in real time, outputting predictions for the front and rear drums, timestamp of the last prediction, and total mass in RASSOR’s drums. Further testing is required to validate the arm-raise model (2), though initial tests indicate reasonable performance (<10% mean error) on the hardware. The linear fit of average drum-current model (3) had a front value of r^2=0.99 and a rear value of r^2=0.98 on the validation dataset. This model currently has the best performance on unseen data. The real time model (4) is still in development, though initial results on a small subset of the training data show that it has high accuracy in predicting the increase in mass during excavation. Though work remains to be done with deploying a high-fidelity model to the physical system that makes predictions with error below the desired threshold, the modular architecture for model development allows quick adjustment of parameters to increase model fidelity. This architecture can also be adapted to use lunar excavation data to create models that are reflective of RASSOR’s dynamics when operating on the lunar surface. The results are promising as it has been shown that models can be developed that accurately estimate excavated regolith mass.

rassor↗

Science Capabilities of the Common Habitat

The Common Habitat is the primary habitable element in a conceptual architecture feasibility study for long-duration space exploration with an eight-person crew size. On lunar or planetary surfaces, the Common Habitat forms the core of a Surface Base Camp. In microgravity, the Common Habitat is the core of the Deep Space Exploration Vehicle (DSEV), an in-space transportation spacecraft. The Common Habitat employs a horizontal orientation that is divided internally into a lower deck, mid deck, and upper deck, roughly separating outfitting into individual, work, and group functions. On a planetary surface, the habitat is incorporated into a base camp, located near the south pole in the case of the Moon. The Mars base camp is currently location agnostic. Each base camp is divided into habitation, landing, resource production, and power zones. In microgravity, the habitat is incorporated into the Deep Space Exploration Vehicle, a vessel capable of transporting the crew within the inner solar system. In addition to crew and teleoperated control of external science assets, the Common Habitat employs a suite of life and physical science laboratory systems to enable it to support science investigations across a variety of destination environments, primarily featuring the Moon and Mars, along with the intervening interplanetary space. Other potential destinations include Near Earth Asteroids and Venus and Earth orbits. Located in the aft starboard section of the Common Habitat mid deck, the life science laboratory supports primarily biology and human research. In its baseline configuration, the laboratory includes horizontal work surfaces, freezers, multiple gloveboxes, sample transfer/exposure capability, large instruments, and reconfigurable ISPR-compatible payload bays. The Medical Care Facility and exercise facility can also support life science research. In the aft port section of the mid deck, the physical science laboratory supports physics, chemistry, materials science, geology, and remote sensing (including astrophysics, heliophysics, Earth science, planetary science, and meteorology). It provides a baseline of similar ISPR-compatible payload bays and adds additional freezers, including those for cryogenic sample storage, a remote sensing workstation, more gloveboxes, also with sample transfer/exposure, combustion chambers, fluid mechanics chambers, and a gas chromatograph. It leverages the Command & Control Center for teleoperations of mobile science assets. Both laboratories are highly modular, with the ability to swap out both payloads and instruments on an as-needed basis. The integrated science outfitting of the Common Habitat positions its crew to contribute to all of NASA’s Moon to Mars science objectives and extend human understanding into the inner solar system.

Lunar Suface↗

Astrobee: Completed, Current, and Future Research using Free Flying Robots on the International Space Station

After four years on the International Space Station (ISS), the Astrobee Research Facility, has completed over 130 Test Sessions logging over 1000 hours of operations. Managed by the NASA ISS Program OZ office and supported by NASA Ames Research Center (ARC) in California, the Astrobee Team maintains three identical free-flying Astrobee robots for research on the ISS. As a technology demonstration platform, the Astrobee Robots are available for Guest Scientists to use for a spectrum of research capabilities. Astrobee, propelled by battery-operated fans, is designed to autonomously operate throughout most of the USOS (US Orbital Segment), with the objective of minimizing astronaut support. Astrobee carries a suite of six cameras, a two degree-of-freedom (DOF) arm with a gripper that can grasp ISS handrails and other objects, and three payload bays that provide power and data for guest science hardware. Astrobee can autonomously execute hours-long flight plans or be teleoperated from the ground or by astronauts. While the Astrobee Team continues to improve mapping and autonomous flight capabilities, one of the main goals of Astrobee Robots is to provide research opportunities for Guest Scientists. The Astrobee Robot Software (ARS) makes extensive use of the open-source Robot Operating System (ROS). The ARS can be used interchangeably with an Astrobee Simulator or as Astrobee’s onboard software. ARS features include autonomous docking and perching, real-time teleoperations from the ground, plan based autonomous tasks, multi Astrobee communication, among other capabilities. Through simulation software and ground testing laboratories, the Astrobee Team is available to support Guest Scientists during development and testing and lead real-time ISS operations. Guest Scientists can participate in this research opportunity following the Guest Science Lifecycle (GSL) shown in Figure 1: Guest Science Lifecycle below. The Astrobee Team and Guest Scientists have complete research including Gecko materials studies, RFID and sound sensing capabilities, student Robotics Programming Challenges, and Free Flyer formation flight investigations. Current science with the Astrobee Robots includes Free Flyer self-toss studies, new docking capabilities, advanced mapping resolution capabilities, and high resolution panoramic imagery. Future Guest scientists and Astrobee Team research will focus on robotics applications for future NASA missions such as Gateway and Artemis and potential experiments involving human-robot interactions. This presentation will focus on four main subjects, 1) completed, current, and future planned research using the Astrobee robots, 2) how Guest Scientist get from conception to the ISS, 3) Astrobee Facility resources available for Guest Science ground testing and real-time ISS operations support, and 4) lessons learned from four years of ISS operations.

Astrobee↗

Mars OASIS (Mars Operational Agricultural System for In-Situ Specialization) System Reference Manual

In order to enable long term habitation on planetary surfaces, a means of sustainable food production must be developed. Addressing this need for surface habitats on Mars, the MarsOASIS team has developed a concept for a Martian surface greenhouse for unmanned crop production research as a proof of concept for larger scale food production facilities for manned surface missions. Utilizing in-situ resources such as the Martian atmosphere, sunlight, and UV-C radiation, the greenhouse aims to provide a sustainable method of long-term food production requiring minimal consumable resources. The MarsOASIS system is capable of growing a full life cycle of Outredgeous lettuce with its autonomous control system designed for a unmanned environment, only requiring teleoperation in extreme circumstances. A reduced-scope prototype of MarsOASIS is being developed to test technologies such as a natural/artificial hybrid lighting system, a closed water recycling system, remote teleoperation, and fully autonomous monitoring and control of the greenhouse. The prototype is currently in the final stages of design, with a full demonstration of plant life cycle testing set to occur in summer 2015. Results from this prototype demonstration will help quantify the feasibility of the innovative approaches seen in the MarsOASIS design.

Asa Darnell↗

Astrobee Operations on the Iss: Gui’S Impact on the Operators’ Cognitive Load

The Astrobee free-flying robots have completed their fifth successful year of operations housed in the Japanese Experimental Module (JEM) on the International Space Station (ISS). In this paper, we introduce two Graphical User Interfaces (GUI) used to operate and monitor in real-time the Astrobee free-flying robots onboard the ISS and report on the impact these GUIs have in the operator’s cognitive load. A review of the state-of-the-art GUI design for remotely teleoperated scenarios with minimal time delay is presented and the study’s conclusion used to determine the elements and recommendations to create an interface that minimizes its impact on the overall performance of an operator during an activity at the ISS. The Ground Data System (GDS) is one of the two GUIs in the study: it contains several tabs, each of which displays a different set of controls for specific tasks e.g. Overview, Run Plan, Teleoperate, Guest Science; some also display video and a three-dimensional (3D) representation of the ISS and robot based on the Astrobee’s telemetry. Most tabs enable a single operator-robot connection, however some of its tabs are capable to monitor and control up to three Astrobees simultaneously. The GDS Helper is a text-based user interface created to facilitate commanding and monitoring of an Astrobee robot directly from an SSH session. In full interactive mode it displays a maximum of 5 sections: general commanding, feedback/ack, telemetry, guest science commanding, and data, all in one view. In batch mode, it enables complex command scripting while retaining some interactive capabilities. A comparative analysis between these GUIs is carried out at an analogous ISS environment at the NASA Ames Research Center’s Granite Lab and its results presented. While GDS is able to provide an operator with control and situational awareness via its video and 3D displays, its several tabs may introduce an overwhelming amount of information confusing and delaying the operator especially during time-sensitive maneuvers where the operator may need to switch back and forth between them. GDS helper in the other hand does not provide video or 3D displays thus not allowing an operator to attain situational awareness, however it provides the operator with a design displaying commonly used data in a single window, enabling the operator to understand the state of the robot at a glance and control it through a commands entered via keyboard instead of a combination of mouse clicks and keyboard input. The results of the experiments measure the cognitive load across several operators maneuvering Astrobee to accomplish tasks ranging from fully manual to supervised activities. A GUI combining a single window displaying data along video and a 3D display is expected to reduce the operator’s cognitive load.

Astrobee↗

Modular Accelerator Robotics Framework Implementation For Accelerator Inspection

Accelerator tunnels, such as the ones at Fermilab, remain highly radioactive after beam shutoff due to induced radiation from the beam. This residual radiation creates a hazardous environment for manual inspection and repair of beamline components. To minimize worker radiation dose and reduce beam downtime, the AD Robotics Initiative previously built a fleet of low-cost custom mobile robots. However, the custom Python sockets server-client architecture lacked standardization, causing development delays and complicating the integration of new sensors and actuators. Here, we developed a modular system using ROS2 and Docker to standardize the teleoperation and control interfaces. This system was validated by implementing a teleoperation controller with real-time, low-latency, and high-definition video feedback. The aim of this framework is for a new feature or even a robot to be integrated into the system simply by documenting the hardware configuration. Current integration of LiDAR, Odometry, and Depth Cameras provides the foundation for Simultaneous Localization and Mapping (SLAM) tasks. Finally, future work involves integration into the accelerator control system and the attachment of a 6 degree-of-freedom robotic arm for telemanipulation.

Rayyan Khana, M. [Unlisted, US, IL] (ORCID:0009000↗

Automation and Robotics for Space-Based Systems, 1991

A NASA Langley workshop on Automation and Robotics for Space-Based Systems was held on December 10, 1991. This conference proceedings document presents the overhead slides from each speaker at this event. The purpose of this in-house workshop was to assess the state-of-the-art of automation and robotics for space operations from a LaRC perspective and to identify areas of opportunity for future research. The workshop was sponsored by the Guidance, Navigation, and Control Technical Committee, chaired by Mr. Raymond C. Montgomery. Nineteen talks were given, reflecting a high level of interest in the field of automation at NASA Langley. Over half of the presentations came from the Automation Technology Branch, covering telerobotic control, EVA and IVA robotics, hand controllers for teleoperation, sensors, neural networks, and automated structural assembly, all applied to space missions. Other talks covered RMS active damping augmentation, space crane work, modeling, simulation, and control of large, flexible space manipulators, and virtual passive controller designs for space robots.

Automation↗

Development of a Commercially Viable, Modular Autonomous Robotic Systems for Converting any Vehicle to Autonomous Control

A Modular Autonomous Robotic System (MARS), consisting of a modular autonomous vehicle control system that can be retrofit on to any vehicle to convert it to autonomous control and support a modular payload for multiple applications is being developed. The MARS design is scalable, reconfigurable, and cost effective due to the use of modern open system architecture design methodologies, including serial control bus technology to simplify system wiring and enhance scalability. The design is augmented with modular, object oriented (C++) software implementing a hierarchy of five levels of control including teleoperated, continuous guidepath following, periodic guidepath following, absolute position autonomous navigation, and relative position autonomous navigation. The present effort is focused on producing a system that is commercially viable for routine autonomous patrolling of known, semistructured environments, like environmental monitoring of chemical and petroleum refineries, exterior physical security and surveillance, perimeter patrolling, and intrafacility transport applications.

guidepath position navigation control system↗

(abstract) An Ada Language Modular Telerobot Task Execution System

A telerobotic task execution system is described which has been developed for space flight applications. The Modular Telerobot Task Execution System (MOTES) provides the remote site task execution capability in a local-remote telerobotic system. The system provides supervised autonomous control, shared control, and teleoperation for a redundant manipulator. The system is capable of nominal task execution as well as monitoring and reflex motion.

robots telerobotics teleoperator autonomous contro↗

Integrated Planning for Telepresence with Time Delays

Integrated planning and execution of teleoperations in space with time delays is shown. The topics include: 1) The Problem; 2) Future Robot Surgery? 3) Approach Overview; 4) Robonaut; 5) Normal Planning and Execution; 6) Planner Context; 7) Implementation; 8) Use of JSHOP2; 9) Monitoring and Testing GUI; 10) Normal sequence: first the supervisor acts; 11) then the robot; 12) Robot might be late; 13) Supervisor can work ahead; 14) Deviations from Plan; 15) Robot State Change Example; 16) Accomplished goals skipped in replan; 17) Planning continuity; 18) Supervisor Deviation From Plan; 19) Intentional Deviation; and 20) Infeasible states.

teleoperation↗

Overview of Space Telerobotics

This chapter discusses the need for space teleoperators and robots, here generically called telerobots, and describes the basic elements of such systems as well as their current capabilities, limitations and need technical improvements.

space↗

Applying Robotics to HAZMAT

The use of robotics in situations involving hazardous materials can significantly reduce the risk of human injuries. The Emergency Response Robotics Project, which began in October 1990 at JPL, is developing a teleoperated mobile robot allowing HAZMAT (hazardous materials) teams to remotely respond to incidents involving hazardous materials. The current robot, called HAZBOT III, can assist in locating, characterizing, identifying, and mitigating hazardous material incidences without risking entry team personnel. The active involvement of the JPL Fire Department HAZMAT team has been vital in developing a robotic system which enables them to perform remote reconnaissance of a HAZMAT incident site. This paper provides a brief review of the history of the project, discusses the current system in detail, and presents other areas in which robotics can be applied, thereby removing people from hazardous environments/operations.

robot↗

Compliant Robotic Behaviors for Satellite Servicing

The demands of traditional industrial robotics differ significantly from those of space robotics. While industry requires robots that can perform repetitive tasks with precision and speed, the space environment needs robots to cope with uncertainties, dynamics, and communication delays or interruptions, similar to human astronauts. These demands make a well-suited application for compliant robotics and behavior-based programming. Pose Target Wrench Limiting (PTWL) is a compliant behavior paradigm developed specifically to meet these demands. PTWL controls a robot by moving a virtual attractor to a target pose. The attractor applies virtual forces, based on stiffness and damping presets, to an underlying admittance controller. Guided by virtual forces, the robot will follow the attractor until safety conditions are violated or success criteria are met. We tested PTWL on a variety of quasi-static tasks that may be useful for future space operations. Our results demonstrate that PTWL is an extremely powerful tool. It makes teleoperation easy and safe for a wide range of quasi-static tasks. It also facilitates the creation of semi-autonomous state machines that can reliably complete complex tasks with minimal human intervention.

Compliance↗