There are many advances in robotics and autonomy depend on increased computational power. Therefore, it is advances in high performance, low power space onboard the computers are central to more capable the robotics. Current efforts in this direction include exploiting high performance field of the programmable gate arrays (FPGAs), multi-core processors, and enabling use in space of commercial grade the computer components through shielding, hardware redundancy, and fault tolerant the software design.
Further pushes in these or other directions to achieve greater in-space computing power are needed. The modular interfaces are needed to enable tool change-out for arms on rovers and for in-space robotics assembly and servicing. When the robots and humans need to work in close proximity; sensing, planning, and autonomous control system for the robots, and overall operational procedures for the robots and humans, it will have to be designed to ensure the human safety around the robots. Developing modular the robotic interfaces will also allow the multiple robots to operate together. These modular interfaces will allow the structural, mechanical, electrical, data, fluid, pneumatic and other interaction. The tools and end effectors can also be developed in a modular manner allowing interchangeability and a reduced the logistics footprint.
The modular interfaces will be the building block for the modular self-replicating robots, and self-assembling robotic systems. The reconfigurable system design offers the ability to reconfigure mechanical, electrical and computing assets in the response to system failures. Reconfigurable computing offers the ability to internally reconfigure in response to the chip level failures caused by the environmental (i.e. space radiation), the life limitations, or the fabrication errors. System verification will be a new challenge for the human rated spacecraft bound for the deep space. New V&V approaches and techniques will be required, and in-flight re-verification following a repair may be necessary.
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Autonomous Rendezvous and Docking of Robotic
AR&D is a capability requiring many vehicle subsystems to operate in concert. It is important to clarify that AR&D is not a system and cannot be purchased off the shelf. This strategy focuses on development of a certified, standardized capability suite of subsystems enabling AR&D for different mission classes and needs. This suite will be incrementally developed, tested and integrated over a span of several missions. This technology roadmap focuses on four specific subsystems required for any AR&D mission.
1. Relative Navigation Sensors – During the course of RPOD, varying accuracies of bearing, range, and relative attitude are needed for AR&D. Current implementations for optical, laser, and RF systems are mid-TRL (Technology Readiness Level) and require some development and flight experience to gain reliability and operational confidence. Inclusion of the ability for cooperating AR&D pairs to communicate directly can greatly improve the responsiveness and robustness of the system.
2. Robust AR&D GN&C Real-Time Flight Software (FSW) – AR&D GN&C algorithms are maturing, however, implementing these algorithms into FSW is an enormous challenge. A best practice based implementation of automated/autonomous GN&C algorithms into real-time FSW operating systems needs to be developed and tested.
3. Docking/Capture – NASA is planning for the imminent construction of a new low-impact docking mechanism built to an international standard for human spaceflight missions to ISS. A smaller common docking system for robotic spacecraft is also needed to enable robotic spacecraft AR&D within the capture envelopes of these systems. Assembly of the large vehicles and stages used for beyond LEO exploration missions will require new mechanisms with new capture envelopes beyond any docking system currently used or in development. Development and testing of autonomous robotic capture of non cooperative target vehicles in which the target does not have capture aids such as grapple fixtures or docking mechanisms is needed to support satellite servicing/rescue.
4. Mission/System Managers – A scalable spacecraft software executive that can be tailored for various mission applications, for the whole vehicle, and various levels of autonomy and automation is needed to ensure safety and operational confidence in AR&D software execution. Numerous spacecraft software executives have been developed, but the necessary piece that is missing is an Agencywide open standard which will minimize the costs of such architectures and its ability to evolve over time to help overcome general fears about autonomy/automation.
1. Relative Navigation Sensors – During the course of RPOD, varying accuracies of bearing, range, and relative attitude are needed for AR&D. Current implementations for optical, laser, and RF systems are mid-TRL (Technology Readiness Level) and require some development and flight experience to gain reliability and operational confidence. Inclusion of the ability for cooperating AR&D pairs to communicate directly can greatly improve the responsiveness and robustness of the system.
2. Robust AR&D GN&C Real-Time Flight Software (FSW) – AR&D GN&C algorithms are maturing, however, implementing these algorithms into FSW is an enormous challenge. A best practice based implementation of automated/autonomous GN&C algorithms into real-time FSW operating systems needs to be developed and tested.
3. Docking/Capture – NASA is planning for the imminent construction of a new low-impact docking mechanism built to an international standard for human spaceflight missions to ISS. A smaller common docking system for robotic spacecraft is also needed to enable robotic spacecraft AR&D within the capture envelopes of these systems. Assembly of the large vehicles and stages used for beyond LEO exploration missions will require new mechanisms with new capture envelopes beyond any docking system currently used or in development. Development and testing of autonomous robotic capture of non cooperative target vehicles in which the target does not have capture aids such as grapple fixtures or docking mechanisms is needed to support satellite servicing/rescue.
4. Mission/System Managers – A scalable spacecraft software executive that can be tailored for various mission applications, for the whole vehicle, and various levels of autonomy and automation is needed to ensure safety and operational confidence in AR&D software execution. Numerous spacecraft software executives have been developed, but the necessary piece that is missing is an Agencywide open standard which will minimize the costs of such architectures and its ability to evolve over time to help overcome general fears about autonomy/automation.
Robotic Autonomous System
Autonomy, in the context of a system (robotic, spacecraft, or aircraft), is the capability for the system to operate independently from external control. For NASA missions there is a spectrum of Autonomy in a system from basic automation (mechanistic execution of action or response to stimuli) through to fully autonomous systems able to act independently in dynamic and uncertain
environments. Two application areas of autonomy are:
(i) increased use of autonomy to enable an independent acting system, and
(ii) automation as an augmentation of human operation. Autonomy’s fundamental benefits are;
increasing a system operations capability, cost savings via increased human labor efficiencies and reduced needs, and increased mission assurance or robustness to uncertain environments.
An “autonomous system” is as a system that resolves choices on its own. The goals the system is trying to accomplish are provided by another entity; thus, the system is autonomous from the entity on whose behalf the goals are being achieved. The decision-making processes may in fact be simple, but the choices are made locally. The selections have been made already, and encoded in some way, or will be made externally to the system Key attributes of such autonomy for a robotic system include the ability for complex decision making, including autonomous mission execution and planning, the ability to self-adapt as the environment in which the system is operating changes, and the ability to understand system state and react accordingly.
Variable (or mixed initiative) autonomy refers to systems in which a user can specify the degree of autonomous control that the system is allowed to take on, and in which this degree of autonomy can be varied from essentially none to near or complete autonomy. For example, in a human-robot system with mixed initiative, the operator may switch levels of autonomy onboard the robot. Controlling levels of autonomy is tantamount to controlling bounds on the robot's authority, response, and operational capabilities.
environments. Two application areas of autonomy are:
(i) increased use of autonomy to enable an independent acting system, and
(ii) automation as an augmentation of human operation. Autonomy’s fundamental benefits are;
increasing a system operations capability, cost savings via increased human labor efficiencies and reduced needs, and increased mission assurance or robustness to uncertain environments.
An “autonomous system” is as a system that resolves choices on its own. The goals the system is trying to accomplish are provided by another entity; thus, the system is autonomous from the entity on whose behalf the goals are being achieved. The decision-making processes may in fact be simple, but the choices are made locally. The selections have been made already, and encoded in some way, or will be made externally to the system Key attributes of such autonomy for a robotic system include the ability for complex decision making, including autonomous mission execution and planning, the ability to self-adapt as the environment in which the system is operating changes, and the ability to understand system state and react accordingly.
Variable (or mixed initiative) autonomy refers to systems in which a user can specify the degree of autonomous control that the system is allowed to take on, and in which this degree of autonomy can be varied from essentially none to near or complete autonomy. For example, in a human-robot system with mixed initiative, the operator may switch levels of autonomy onboard the robot. Controlling levels of autonomy is tantamount to controlling bounds on the robot's authority, response, and operational capabilities.
Robonaut 2 Mission to ISS
During FY11 the Robonaut 2 system will be launched on STS-133 and delivered to the ISS in what will become the Permanent Multipurpose Module (PMM). Robonaut 2 (R2) is the latest in a series of dexterous robots built by NASA as technology demonstration, nowevolving from Earth to in-space experiments. The main objectives are to explore dexterous manipulation in zero gravity, test human-robot safety systems, test remote supervision techniques for operation across time delays, and experiment with ISS equipment to begin offloading crew of housekeeping and other chores. The R2 was built in a partnership with General Motors, with a shared vision of a capable but safe robot working near people.
The R2 has the state of the art in tactile sensing and perception, as well as depth map sensors, stereo vision, and force sensing. The R2 will be deployed initially on a fixed pedestal with zero mobility, but future upgrades are planned to allow it to climb and reposition itself at different worksites. Robonaut 2’s dexterous manipulators are the state of the art, with three levels of force sensing for safety, high strength to weight ratios, compliant and back drivable drive trains, soft and smooth coverings, fine force and position control, dual arm coordination, and kinematic redundancy.
Human interfaces for the R2 include direct force interaction where humans can manually position the limbs, trajectory design software tools, and script engines. R2 is designed to be directly tele-operated, remotely supervised, or run in an automated manner. The modular design can be upgraded over time to extend the Robonaut capabilities with new limbs, backpacks, sensors and software.
The Robotic Refueling Dexterous Demonstration (R2D2) is a multifaceted payload designed for representative tasks required to robotically refuel a spacecraft. Once mounted to the International Space Station, the demonstration will utilize the R2D2 payload complement, the Special Purpose Dexterous Manipulator (SPDM) robotic arms, and 4 customized, interchangeable tools to simulate the tasks needed to refuel a spacecraft using its standard ground fill‐and‐drain valve.
The R2 has the state of the art in tactile sensing and perception, as well as depth map sensors, stereo vision, and force sensing. The R2 will be deployed initially on a fixed pedestal with zero mobility, but future upgrades are planned to allow it to climb and reposition itself at different worksites. Robonaut 2’s dexterous manipulators are the state of the art, with three levels of force sensing for safety, high strength to weight ratios, compliant and back drivable drive trains, soft and smooth coverings, fine force and position control, dual arm coordination, and kinematic redundancy.
Human interfaces for the R2 include direct force interaction where humans can manually position the limbs, trajectory design software tools, and script engines. R2 is designed to be directly tele-operated, remotely supervised, or run in an automated manner. The modular design can be upgraded over time to extend the Robonaut capabilities with new limbs, backpacks, sensors and software.
The Robotic Refueling Dexterous Demonstration (R2D2) is a multifaceted payload designed for representative tasks required to robotically refuel a spacecraft. Once mounted to the International Space Station, the demonstration will utilize the R2D2 payload complement, the Special Purpose Dexterous Manipulator (SPDM) robotic arms, and 4 customized, interchangeable tools to simulate the tasks needed to refuel a spacecraft using its standard ground fill‐and‐drain valve.
Mobility in Robotic Space
The state of the art in robotic space mobility (e.g. not including conventional rocket propulsion) includes the Mars Exploration Rovers and the upcoming Mars Science Laboratory, and for human surface mobility the Apollo lunar roving vehicle used on the final three Apollo missions. Recently, systems have been developed and tested on Earth for mobility on planetary surfaces including the Space Exploration Vehicle and the ATHLETE wheel-on-leg cargo transporter. Both feature active suspension. A series of grand challenges have extended the reach of robotic off-road mobility to high speeds and progressively more extreme terrain.
For microgravity mobility, the Manned Maneuvering Unit (MMU), tested in 1984 and, more recently, the SAFER jet pack provide individual astronauts with the ability to move and maneuver in free space, or in the neighborhood of a Near-Earth Asteroid. The AERCam system flew on STS-87 in 1997 as the first of future small free-flying inspection satellites. We can expect in the next few decades that robotic vehicles designed for planetary surfaces will approach or even exceed the performance of the best piloted human vehicles on Earth in traversing extreme terrain and reaching sites of interest despite severe terrain challenges.
Human drivers have a remarkable ability to perceive terrain hazards at long range and to pilot surface vehicles along dynamic trajectories that seem nearly optimal. Despite the limitations of human sensing and cognition, it is generally observed that experienced drivers can pilot their vehicles at speeds near the limits set by physical law (e.g. frictional coefficients, tipover and other vehicle-terrain kinematic and dynamic failures). This fact is remarkable given the huge computational throughput requirements needed to quickly assess subtle terrain geometric and non-geometric properties (e.g. visually estimating the properties of soft soil) at long range fast enough to maintain speeds near the vehicle limits. This ability is lacking in today’s best obstacle detection and hazard avoidance systems.
For microgravity mobility, the Manned Maneuvering Unit (MMU), tested in 1984 and, more recently, the SAFER jet pack provide individual astronauts with the ability to move and maneuver in free space, or in the neighborhood of a Near-Earth Asteroid. The AERCam system flew on STS-87 in 1997 as the first of future small free-flying inspection satellites. We can expect in the next few decades that robotic vehicles designed for planetary surfaces will approach or even exceed the performance of the best piloted human vehicles on Earth in traversing extreme terrain and reaching sites of interest despite severe terrain challenges.
Human drivers have a remarkable ability to perceive terrain hazards at long range and to pilot surface vehicles along dynamic trajectories that seem nearly optimal. Despite the limitations of human sensing and cognition, it is generally observed that experienced drivers can pilot their vehicles at speeds near the limits set by physical law (e.g. frictional coefficients, tipover and other vehicle-terrain kinematic and dynamic failures). This fact is remarkable given the huge computational throughput requirements needed to quickly assess subtle terrain geometric and non-geometric properties (e.g. visually estimating the properties of soft soil) at long range fast enough to maintain speeds near the vehicle limits. This ability is lacking in today’s best obstacle detection and hazard avoidance systems.
Human-Systems Interfaces of Space Robotic
The ultimate efficacy of space systems depends greatly upon the interfaces that humans use to operate them. The current state of the art in human system interfaces is summarized below along with some of the advances that are expected in the next 25 years. Human operation of most systems today is accomplished in a simple pattern reminiscent of the classic “Sense – Plan – Act” control paradigm for robotics and remotely operated systems. The human observes the state of the system and its environment, forms a mental plan for its future action, and then commands the robot or machine to execute that plan. Most of the recent work in this field is focused on providing tools to more effectively communicate state to the human and capture commands for the robot, each of which is discussed in more detail below.
Current human-system interfaces typically include software applications that communicate internal system state via abstract gauges and readouts reminiscent of aircraft cockpits or overlays on realistic illustrations of the physical plant and its components. Information from sensors is available in its native form (for instance, a single image from a camera) and aggregated into a navigable model of the environment that may contain data from multiple measurements and sensors. Some interfaces are adapted to immersive displays, mobile devices, or allow multiple distributed operators to monitor the remote system simultaneously.
Future interfaces will communicate state through increased use of immersive displays, creating“Holodeck”-like virtual environments that can be naturally explored by the human operator with “Avatar”-like telepresence. These interfaces will also more fully engage the aural and tactile senses of the human to communicate more information about the state of the robot and its surroundings. As robots grow increasingly autonomous, improved techniques for communicating the “mental state” of robots will be introduced, as well as mechanisms for understanding the dynamic state of reconfigurable robots and complex sensor data from swarms.
Current human-robot interfaces typically allow for two types of commands. The first are simple, brief directives, sometimes sent via specialized control devices such as joysticks, which interrupt
existing commands and immediately affect the state of the robot. A few interfaces allow the issuance of these commands through speech and gestures.
Current human-system interfaces typically include software applications that communicate internal system state via abstract gauges and readouts reminiscent of aircraft cockpits or overlays on realistic illustrations of the physical plant and its components. Information from sensors is available in its native form (for instance, a single image from a camera) and aggregated into a navigable model of the environment that may contain data from multiple measurements and sensors. Some interfaces are adapted to immersive displays, mobile devices, or allow multiple distributed operators to monitor the remote system simultaneously.
Future interfaces will communicate state through increased use of immersive displays, creating“Holodeck”-like virtual environments that can be naturally explored by the human operator with “Avatar”-like telepresence. These interfaces will also more fully engage the aural and tactile senses of the human to communicate more information about the state of the robot and its surroundings. As robots grow increasingly autonomous, improved techniques for communicating the “mental state” of robots will be introduced, as well as mechanisms for understanding the dynamic state of reconfigurable robots and complex sensor data from swarms.
Current human-robot interfaces typically allow for two types of commands. The first are simple, brief directives, sometimes sent via specialized control devices such as joysticks, which interrupt
existing commands and immediately affect the state of the robot. A few interfaces allow the issuance of these commands through speech and gestures.
Tele-Robotics and Autonomous Systems Technology Area Breakdown Structure
The Robotics, Tele-Robotics and Autonomous Systems Technology Area Breakdown Structure (TABS). This area includes sensors and algorithms needed to convert sensor data into representations suitable for decision-making. Traditional spacecraft sensing and perception included position, attitude, and velocity estimation in reference frames centered on solar system bodies, plus sensing spacecraft internal degrees of freedom, such as scan-platform angles. Current and future development will expand this to include position, attitude, and velocity estimation relative to local terrain, plus rich perception of characteristics of local terrain — where “terrain” may include the structure of other spacecraft in the vicinity and dynamic events, such as atmospheric phenomena.
Enhanced sensing and perception will broadly impact three areas of capability: autonomous navigation, sampling and manipulation, and interpretation of science data. In autonomous navigation, 3-D perception has already been central to autonomous navigation of planetary rovers. Current capability focuses on stereoscopic 3-D perception in daylight. Active optical ranging (LIDAR) is commonly used in Earthbased robotic systems and is under development for landing hazard detection in planetary exploration. Progress is necessary in increasing the speed, resolution, and field of regard of such sensors, reducing their size, weight, and power, enabling night operation, and hardening them for flight.
Range and imagery data is already in some use for rover and lander position and velocity estimation, though with relatively slow update rates. Realtime, onboard 3-D perception, mapping, and terrain-relative position and velocity estimation capability is also needed for small body proximity operation, balloons and airships, and micro-inspector spacecraft. For surface navigation, sensing and perception must be extended from 3-D. Perception to estimating other terrain properties pertinent to trafficability analysis, such as softness of soil or depth to the load-bearing surface. Many types of sensors may be relevant to this task, including contact and remote sensors onboard rovers and remote sensors on orbiters.
Sampling generally refers to handling natural materials in scientific exploration; manipulation includes actions needed in sampling and handling man-made objects, including sample containers in scientific exploration and handling a variety of tools and structures during robotic assembly and maintenance. 3-D perception, mapping, and relative motion estimation are also relevant here. Non-geometric terrain property estimation is also relevant to distinguish where and how to sample, as well as where and how to anchor to surfaces in micro-gravity or to steep slopes on large bodies.
Enhanced sensing and perception will broadly impact three areas of capability: autonomous navigation, sampling and manipulation, and interpretation of science data. In autonomous navigation, 3-D perception has already been central to autonomous navigation of planetary rovers. Current capability focuses on stereoscopic 3-D perception in daylight. Active optical ranging (LIDAR) is commonly used in Earthbased robotic systems and is under development for landing hazard detection in planetary exploration. Progress is necessary in increasing the speed, resolution, and field of regard of such sensors, reducing their size, weight, and power, enabling night operation, and hardening them for flight.
Range and imagery data is already in some use for rover and lander position and velocity estimation, though with relatively slow update rates. Realtime, onboard 3-D perception, mapping, and terrain-relative position and velocity estimation capability is also needed for small body proximity operation, balloons and airships, and micro-inspector spacecraft. For surface navigation, sensing and perception must be extended from 3-D. Perception to estimating other terrain properties pertinent to trafficability analysis, such as softness of soil or depth to the load-bearing surface. Many types of sensors may be relevant to this task, including contact and remote sensors onboard rovers and remote sensors on orbiters.
Sampling generally refers to handling natural materials in scientific exploration; manipulation includes actions needed in sampling and handling man-made objects, including sample containers in scientific exploration and handling a variety of tools and structures during robotic assembly and maintenance. 3-D perception, mapping, and relative motion estimation are also relevant here. Non-geometric terrain property estimation is also relevant to distinguish where and how to sample, as well as where and how to anchor to surfaces in micro-gravity or to steep slopes on large bodies.
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