SEARCH · Search NASA

Results for “human-robot interaction”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

SourceResearch connectionFrom yearThrough year

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 19 records

All sources NASA NTRS DOE OSTI

NASA NTRS2004

Peer-to-Peer Human-Robot Interaction for Space Exploration

NASA has embarked on a long-term program to develop human-robot systems for sustained, affordable space exploration. To support this mission, we are working to improve human-robot interaction and performance on planetary surfaces. Rather than building robots that function as glorified tools, our focus is to enable humans and robots to work as partners and peers. In this paper. we describe our approach, which includes contextual dialogue, cognitive modeling, and metrics-based field testing.

Fong, Terrence↗

NASA NTRS1991

On the role of exchange of power and information signals in control and stability of the human-robot interaction

A human's ability to perform physical tasks is limited, not only by his intelligence, but by his physical strength. If, in an appropriate environment, a machine's mechanical power is closely integrated with a human arm's mechanical power under the control of the human intellect, the resulting system will be superior to a loosely integrated combination of a human and a fully automated robot. Therefore, we must develop a fundamental solution to the problem of 'extending' human mechanical power. The work presented here defines 'extenders' as a class of robot manipulators worn by humans to increase human mechanical strength, while the wearer's intellect remains the central control system for manipulating the extender. The human, in physical contact with the extender, exchanges power and information signals with the extender. The aim is to determine the fundamental building blocks of an intelligent controller, a controller which allows interaction between humans and a broad class of computer-controlled machines via simultaneous exchange of both power and information signals. The prevalent trend in automation has been to physically separate the human from the machine so the human must always send information signals via an intermediary device (e.g., joystick, pushbutton, light switch). Extenders, however are perfect examples of self-powered machines that are built and controlled for the optimal exchange of power and information signals with humans. The human wearing the extender is in physical contact with the machine, so power transfer is unavoidable and information signals from the human help to control the machine. Commands are transferred to the extender via the contact forces and the EMG signals between the wearer and the extender. The extender augments human motor ability without accepting any explicit commands: it accepts the EMG signals and the contact force between the person's arm and the extender, and the extender 'translates' them into a desired position. In this unique configuration, mechanical power transfer between the human and the extender occurs because the human is pushing against the extender. The extender transfers to the human's hand, in feedback fashion, a scaled-down version of the actual external load which the extender is manipulating. This natural feedback force on the human's hand allows him to 'feel' a modified version of the external forces on the extender. The information signals from the human (e.g., EMG signals) to the computer reflect human cognitive ability, and the power transfer between the human and the machine (e.g., physical interaction) reflects human physical ability. Thus the information transfer to the machine augments cognitive ability, and the power transfer augments motor ability. These two actions are coupled through the human cognitive/motor dynamic behavior. The goal is to derive the control rules for a class of computer-controlled machines that augment human physical and cognitive abilities in certain manipulative tasks.

Kazerooni, H.↗

NASA NTRS2001

Human-Vehicle Interface for Semi-Autonomous Operation of Uninhabited Aero Vehicles

The robustness of autonomous robotic systems to unanticipated circumstances is typically insufficient for use in the field. The many skills of human user often fill this gap in robotic capability. To incorporate the human into the system, a useful interaction between man and machine must exist. This interaction should enable useful communication to be exchanged in a natural way between human and robot on a variety of levels. This report describes the current human-robot interaction for the Stanford HUMMINGBIRD autonomous helicopter. In particular, the report discusses the elements of the system that enable multiple levels of communication. An intelligent system agent manages the different inputs given to the helicopter. An advanced user interface gives the user and helicopter a method for exchanging useful information. Using this human-robot interaction, the HUMMINGBIRD has carried out various autonomous search, tracking, and retrieval missions.

Jones, Henry L.↗

DOE OSTI2026

CRCNS21 Computational Models of Multisensory Integration by Upper Limb in Humanoids and Amputees

This international collaborative research project between Johns Hopkins University (JHU) and the Technical University of Munich (TUM) investigated how the human brain processes and integrates multiple types of sensory information, such as touch and force, with the goal of improving prosthetic limbs for amputees and advancing sensory capabilities in humanoid robots. The research advanced our understanding of how the brain responds to sensory feedback in upper-limb amputees. Through experiments in which amputees received electrical stimulation while performing phantom hand movements, we demonstrated that sensory feedback activates the cortical sensorimotor and multisensory regions, and that these regions communicate dynamically during stimulation. Experiments with intact-limb participants explored the integration of visual, haptic, and force feedback, as well as in virtual reality motor training, further showing how the brain processes multimodal sensory information. In addition, this research inspired work on examining the reliability of where amputees perceive sensations over time, which contributed to a successful doctoral fellowship for continued investigation. Our collaborators at TUM improved multimodal sensor technology combining tactile and thermal feedback for humanoid robots, demonstrating the feasibility of integrating multiple sensor types into a unified system for detecting and responding to environmental stimuli. The experimental methods and analysis techniques developed across both teams, including functional network analysis and multimodal sensor integration, provide a foundation for future research in prosthetics and robotics. This research benefits the public by generating knowledge about how amputees process restored sensory information. Advances in humanoid sensing contribute to safer human-robot interaction. The project also fostered international collaboration and cross-disciplinary training: one TUM doctoral student spent a summer at JHU working on multimodal sensor integration, while two JHU students traveled to TUM to host workshops on neuromorphic sensory encoding and sensory integration.

42 ENGINEERING↗

NASA NTRS1988

Design of a simulation environment for laboratory management by robot organizations

This paper describes the basic concepts needed for a simulation environment capable of supporting the design of robot organizations for managing chemical, or similar, laboratories on the planned U.S. Space Station. The environment should facilitate a thorough study of the problems to be encountered in assigning the responsibility of managing a non-life-critical, but mission valuable, process to an organized group of robots. In the first phase of the work, we seek to employ the simulation environment to develop robot cognitive systems and strategies for effective multi-robot management of chemical experiments. Later phases will explore human-robot interaction and development of robot autonomy.

Zeigler, Bernard P.↗

NASA NTRS1990

Telefunctioning - An approach to telerobotic manipulations

This study introduces three concepts: telefunctioning, a control method for achieving telefunctioning, and an approach to the analysis of human-robot interaction when telefunctioning governs the system behavior. Telefunctioning facilitates maneuvering of loads by creating a perpetual sense of the load dynamics for the operator. Telefunctioning is defined as a robotic manipulation method in which the dynamic behaviors of the slave robot and the master robot are functions of each other; these functions are the designer's choice and depend on the application. In a subclass of telefunctioning called telepresence, all of the relationships between the master and the slave are specified as unity so that all of the master and slave variables (e.g., position and velocity) are dynamically equal. To create telefunctioning, a minimum number of functions relating the robots' variables is identified. A control architecture which guarantees that the defined functions govern the dynamic behavior of the system is then developed. The stability of the closed-loop system (master robot, slave robot, human, and the load being manipulated) is analyzed, and sufficient conditions for stability are derived.

Kazerooni, H.↗

NASA NTRS2002

Manipulability, force, and compliance analysis for planar continuum manipulators

Continuum manipulators, inspired by the natural capabilities of elephant trunks and octopus tentacles, may find niche applications in areas like human-robot interaction, multiarm manipulation, and unknown environment exploration. However, their true capabilities will remain largely inaccessible without proper analytical tools to evaluate their unique properties. Ellipsoids have long served as one of the foremost analytical tools available to the robotics researcher, and the purpose of this paper is to first formulate, and then to examine, three types of ellipsoids for continuum robots: manipulability, force, and compliance.

Non-NASA Center↗

NASA NTRS2004

Robotic Assistance for Human Planetary and Lunar Exploration

Human exploration of space will need robotic assistance in many areas. The type and functionality of such robots needs to be more clearly defined as we resume human missions to the moon and begin human missions to Mars. This paper will identify possible robotic assistants, including their control modes, workplaces, and physical attributes. Current JSC human-robot interaction projects are described, and lessons learned from extensive field tests are given. Future scenario considerations are then detailed. Earth-based testing of varied robotic assistants will provide a means of defining what capabilities are needed for future exploration.

Tyree, Kimberly S.↗

NASA NTRS2004

Robotic Assistance for Human Planetary and Lunar Exploration

Tyree, Kimberly S.↗

NASA NTRS2003

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↗

NASA NTRS2004

Human-Robot Planetary Exploration Teams

The EVA Robotic Assistant (ERA) project at NASA Johnson Space Center studies human-robot interaction and robotic assistance for future human planetary exploration. Over the past four years, the ERA project has been performing field tests with one or more four-wheeled robotic platforms and one or more space-suited humans. These tests have provided experience in how robots can assist humans, how robots and humans can communicate in remote environments, and what combination of humans and robots works best for different scenarios. The most efficient way to understand what tasks human explorers will actually perform, and how robots can best assist them, is to have human explorers and scientists go and explore in an outdoor, planetary-relevant environment, with robots to demonstrate what they are capable of, and roboticists to observe the results. It can be difficult to have a human expert itemize all the needed tasks required for exploration while sitting in a lab: humans do not always remember all the details, and experts in one arena may not even recognize that the lower level tasks they take for granted may be essential for a roboticist to know about. Field tests thus create conditions that more accurately reveal missing components and invalid assumptions, as well as allow tests and comparisons of new approaches and demonstrations of working systems. We have performed field tests in our local rock yard, in several locations in the Arizona desert, and in the Utah desert. We have tested multiple exploration scenarios, such as geological traverses, cable or solar panel deployments, and science instrument deployments. The configuration of our robot can be changed, based on what equipment is needed for a given scenario, and the sensor mast can even be placed on one of two robot bases, each with different motion capabilities. The software architecture of our robot is also designed to be as modular as possible, to allow for hardware and configuration changes. Two focus areas of our research are safety and crew time efficiency. For safety, our work involves enabling humans to reliably communicate with a robot while moving in the same workspace, and enabling robots to monitor and advise humans of potential problems. Voice, gesture, remote computer control, and enhanced robot intelligence are methods we are studying. For crew time efficiency, we are investigating the effects of assigning different roles to humans and robots in collaborative exploration scenarios.

Tyree, Kimberly↗

NASA NTRS2004

Desert Research and Technology Study 2003 Trip Report/ICES Paper

The Advanced Extra-vehicular Activity (EVA) team of the National Aeronautics and Space Administration (NASA) Johnson Space Center (JSC) Crew and Thermal Systems Division (CTSD) participated in the Desert Research and Technology Study (RATS) in September 2003, at Meteor Crater, AZ. The Desert RATS is an integrated remote field site te t with team members from several NASA centers (Johnson Space Center; Glenn and Ames Research Centers) and universities (Bowling Green State University, University of Cincinnati, Massachusetts Institute of Technology) participating. Each week of the two-week field test had a primary focus. The primary test hardware for the first week was the I-Gravity Lunar Rover Training Vehicle, or Grover, which was on loan to NASA from the United States Geological Survey (USGS) Astrogeology Research Program. The 2003 Grover driving test results serve as a rover performance characterization baseline for the Science, Crew, Operation and Utility Testbed (SCOUT) project team, which will be designing and fabricating a next generation roving vehicle prototype in Fiscal Year (FY) 2004. The second week of testing focused on EVA geologic traverses that utilized a geologic sample field analysis science trailer and also focused on human-robotic interaction between the suited subjects and the EVA Robotic Assistant (ERA). This paper will review the Advanced EVA team's role in the context of the overall Desert RATS, as well as the EVA team results and lessons learned. For information regarding other test participants' results, the authors can refer interested parties to the test reports produced by those Desert RATS teams.

Ross, Amy↗

NASA NTRS2005

Interaction Challenges in Human-Robot Space Exploration

In January 2004, NASA established a new, long-term exploration program to fulfill the President's Vision for U.S. Space Exploration. The primary goal of this program is to establish a sustained human presence in space, beginning with robotic missions to the Moon in 2008, followed by extended human expeditions to the Moon as early as 2015. In addition, the program places significant emphasis on the development of joint human-robot systems. A key difference from previous exploration efforts is that future space exploration activities must be sustainable over the long-term. Experience with the space station has shown that cost pressures will keep astronaut teams small. Consequently, care must be taken to extend the effectiveness of these astronauts well beyond their individual human capacity. Thus, in order to reduce human workload, costs, and fatigue-driven error and risk, intelligent robots will have to be an integral part of mission design.

Fong, Terrence↗

NASA NTRS2004

Applications of Intelligent Tutoring Systems to Human-Robotic Exploration of Mars

Space missions with small crews extending over several years with time-delay preventing normal conversations with people on earth will raise many challenges for training. Of special interest are possible three-year missions to Mars, requiring refresher instruction and learning new skills based on unexpected problems with machines and environmental conditions. For example, the crew will be required to monitor and repair more complex life support systems for air and water recycling than we even know how to build today. Highly educated astronauts, often with several doctorate degrees, require a very different mode of interaction than we have developed for school children or even typical college students. Explanation methods may need to differ-using analogies and techniques from different domains-depending on whether the astronaut is an astrophysicist, a pilot, or a geologist.Virtual reality (e.g., for Hubble repair missions) and "integrated" simulations (involving role-playing and emphasizing failure scenarios) are the most common advanced forms of instruction used in space flight today. The emphasis is on collaborative, embodied interaction with the same workstations and tools used in practice (e.g., a cockpit simulator). Otherwise, computerized instructional technology used by NASA is not model-based or tutorial in nature. This discussion will review some of the key instructional methods used at NASA over the past two decades and consider why ITS methods have not been exploited. Some of the problems and opportunities for training for Mars missions are examined, including how using robots in exploration activities will help but raise new training problems. These ideas will be illustrated with examples from the BrahmsVE system in which a browser- based virtual reality display with avatars allows interacting with a distributed multiagent system, in which agents can be people, robots, or software programs. Using BrahmsVE may provide a way for astronauts to interact with proxies of people who serve as instructional coaches on Mars.

Clancey, William J.↗

NASA NTRS2004

Advanced Integration Matrix Education Outreach

The Advanced Integration Matrix (AIM) will design a ground-based test facility for developing revolutionary integrated systems for joint human-robotic missions in order to study and solve systems-level integration issues for exploration missions beyond Low Earth Orbit (LEO). This paper describes development plans for educational outreach activities related to technological and operational integration scenarios similar to the challenges that will be encountered through this project. The education outreach activities will provide hands-on, interactive exercises to allow students of all levels to experience design and operational challenges similar to what NASA deals with everyday in performing the integration of complex missions. These experiences will relate to and impact students everyday lives by demonstrating how their interests in science and engineering can develop into future careers, and reinforcing the concepts of teamwork and conflict resolution. Allowing students to experience and contribute to real-world development, research, and scientific studies of ground-based simulations for complex exploration missions will stimulate interest in the space program, and bring NASA's challenges to the student level. By enhancing existing educational programs and developing innovative activities and presentations, AIM will support NASA s endeavor to "inspire the next generation of explorers.. .as only NASA can."

Paul Heather L.↗

NASA NTRS2005

Towards the Verification of Human-Robot Teams

Human-Agent collaboration is increasingly important. Not only do high-profile activities such as NASA missions to Mars intend to employ such teams, but our everyday activities involving interaction with computational devices falls into this category. In many of these scenarios, we are expected to trust that the agents will do what we expect and that the agents and humans will work together as expected. But how can we be sure? In this paper, we bring together previous work on the verification of multi-agent systems with work on the modelling of human-agent teamwork. Specifically, we target human-robot teamwork. This paper provides an outline of the way we are using formal verification techniques in order to analyse such collaborative activities. A particular application is the analysis of human-robot teams intended for use in future space exploration.

Fisher, Michael↗

NASA NTRS2002

Simulating Activities: Relating Motives, Deliberation and Attentive Coordination

Activities are located behaviors, taking time, conceived as socially meaningful, and usually involving interaction with tools and the environment. In modeling human cognition as a form of problem solving (goal-directed search and operator sequencing), cognitive science researchers have not adequately studied "off-task" activities (e.g., waiting), non-intellectual motives (e.g., hunger), sustaining a goal state (e.g., playful interaction), and coupled perceptual-motor dynamics (e.g., following someone). These aspects of human behavior have been considered in bits and pieces in past research, identified as scripts, human factors, behavior settings, ensemble, flow experience, and situated action. More broadly, activity theory provides a comprehensive framework relating motives, goals, and operations. This paper ties these ideas together, using examples from work life in a Canadian High Arctic research station. The emphasis is on simulating human behavior as it naturally occurs, such that "working" is understood as an aspect of living. The result is a synthesis of previously unrelated analytic perspectives and a broader appreciation of the nature of human cognition. Simulating activities in this comprehensive way is useful for understanding work practice, promoting learning, and designing better tools, including human-robot systems.

Clancey, William J.↗

NASA NTRS2003

Robot Tracking of Human Subjects in Field Environments

Future planetary exploration will involve both humans and robots. Understanding and improving their interaction is a main focus of research in the Intelligent Systems Branch at NASA's Johnson Space Center. By teaming intelligent robots with astronauts on surface extra-vehicular activities (EVAs), safety and productivity can be improved. The EVA Robotic Assistant (ERA) project was established to study the issues of human-robot teams, to develop a testbed robot to assist space-suited humans in exploration tasks, and to experimentally determine the effectiveness of an EVA assistant robot. A companion paper discusses the ERA project in general, its history starting with ASRO (Astronaut-Rover project), and the results of recent field tests in Arizona. This paper focuses on one aspect of the research, robot tracking, in greater detail: the software architecture and algorithms. The ERA robot is capable of moving towards and/or continuously following mobile or stationary targets or sequences of targets. The contributions made by this research include how the low-level pose data is assembled, normalized and communicated, how the tracking algorithm was generalized and implemented, and qualitative performance reports from recent field tests.

Graham, Jeffrey↗