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Astrobee is a new class of free-flying robots that operate in the interior of the International Space Station (ISS). In addition to providing a research platform for zero-g free-flying robotics (replacing the Synchronized Position Hold Engage and Reorient Experimental Satellites (SPHERES)), Astrobee improves the efficiency of ISS operations by providing flight and payload controllers with a mobile camera/sensor platform. The Astrobee system consists of three robots, a docking station, and a ground data system. Development began in late 2014, and Astrobee will launch to ISS in late 2018. This paper provides an overview of the capabilities of the Astrobee system, the concept of operations for ISS operations support, and the challenges of operating a free-flying robot within the constraints of the ISS environment.

Robotic reconnaissance (“recon”) has the potential to significantly improve scientific and technical return from lunar surface exploration. In particular, robotic recon can be used to improve traverse planning, reduce operational risk, and increase crew productivity. To study how robotic recon can benefit human exploration, we recently conducted a field experiment at Black Point Lava Flow (BPLF), Arizona. In our experiment, a simulated ground control team at NASA Ames teleoperated a planetary rover to scout geology traverses at BPLF. The recon data were then used to plan revised traverses. Two-man crews subsequently performed both types of traverses using the NASA “Lunar Electric Rover” (LER) and simulated extra-vehicular activity (EVA) suits. This paper describes the design of our experiment, presents our results, and discusses directions for future research.

Astronaut time will always be in short supply, consumables (e.g., oxygen) will always be limited, and some work will not be feasible, or productive, for astronauts to do manually. Free flyers offer significant potential to perform a great variety of tasks, include routine, repetitive or simple but long-duration work, such as conducting environment surveys, taking sensor readings or monitoring crew activities. The "Astrobee" project is developing a new free flying robot system suitable for performing Intravehicular Activity (IVA) work on the International Space Station (ISS). This paper will describe the Astrobee project objectives, initial design, concept of operations, and key challenges.

Nomad was deployed for a 45 day traverse in the Atacama Desert, Chile, during the summer of 1997. During this traverse, 1 week was devoted to science experiments. The goal of the science experiments was to test different planetary surface exploration strategies that included (1) a Mars mission simulation, (2) a science on the fly experiment, where the rover was kept moving 75% of the operation time. (The goal of this operation was to determine whether or not successful interpretation of the environment is related to the time spent on a target. The role of mobility in helping the interpretation was also assessed.) (3) a meteorite search using visual and instrumental methods to remotely identify meteorites in extreme environments, and (4) a time-delay experiment with and without using the panospheric camera. The results were as follow: the remote science team positively identified the main characteristics of the test site geological environment. The science on the fly experiment showed that the selection of appropriate targets might be even more critical than the time spent on a study area to reconstruct the history of a site. During the same operation the science team members identified and sampled a rock from a Jurassic outcrop that they proposed to be a fossil. The presence of paleolife indicators in this rock was confirmed later by laboratory analysis. Both visual and instrumental modes demonstrated the feasibility, in at least some conditions, of carrying out a field search for meteorites by using remote-controlled vehicles. Finally, metrics collected from the observation of the science team operations, and the use team members made of mission data, provided critical information on what operation sequences could be automated on board rovers in future planetary surface explorations.

The Autonomy and Robotics Area (ARA) at NASA Ames Research Center has investigated the use of various types of Virtual Reality-based operator interfaces to remotely control complex robotic mechanisms. In this paper, we describe the major accomplishments and technology applications of the ARA in this area, and highlight the advantages and issues related to this technology.

In planning for future exploration missions, architecture and study teams have made numerous assumptions about how crew can be telepresent on a planetary surface by remotely operating surface robots from space (i.e. from a flight vehicle or deep space habitat). These assumptions include estimates of technology maturity, existing technology gaps, and operational risks. These assumptions, however, have not been grounded by experimental data. Moreover, to date, no crew-controlled surface telerobot has been fully tested in a high-fidelity manner. To address these issues, we developed the "Surface Telerobotics" tests to do three things: 1) Demonstrate interactive crew control of a mobile surface telerobot in the presence of short communications delay. 2) Characterize a concept of operations for a single astronaut remotely operating a planetary rover with limited support from ground control. 3) Characterize system utilization and operator work-load for a single astronaut remotely operating a planetary rover with limited support from ground control.

Robotic rovers can be used as advance scouts to signifi cantly improve scientifi c and technical return of planetary surface exploration. Robotic scouting, or “robotic recon,” involves using a robot to collect ground-level data prior to human fi eld activity. The data collected and knowledge acquired through recon can be used to refi ne traverse planning, reduce operational risk, and increase crew productivity. To understand how robotic recon can benefi t human exploration, we conducted a series of simulated planetary robotic missions at analog sites. These mission simulations were designed to: (1) identify and quantify operational requirements for robotic recon in advance of human activity; (2) identify and quantify ground control and science team requirements for robotic recon; and (3) identify capability, procedure, and training requirements for human explorers to draw maximum benefi t from robotic recon during vehicular traverses and on-foot extravehicular activities (EVA). Our studies indicate that robotic recon can be benefi cial to crew, improving preparation, situational awareness, and productivity in the fi eld. This is particularly true when traverse plans contain signifi cant unknowns that can be resolved by recon, such as target access and station/activity priority. In this paper, we fi rst present the assumptions and major questions related to robotic reconnaissance. We detail our system design, including the confi guration of our recon robot, the ground data system used for operation, ground control organization, and operational time lines. Finally, we describe the design and results from an experiment to assess robotic recon, discuss lessons learned, and identify directions for future work.

By 2020, NASA plans to return to the Moon with a new series of regularly spaced surface missions. Crewed missions will initially be "extended sortie" (e.g., 1-2 weeks). During the first few years of the lunar campaign, humans will be on the Moon less than 10% of the time. During the 90% of time between crew visits, robots could perform tasks under ground control. This paper presents the system design for a prototype robotic recon robot and ground control approach, as well as a terrestrial analog field test designed to assess the utility of recon for augmenting and assisting human exploration of a lunar-like environment. Results are presented for recent field testing of the reconnaissance robot in northern Arizona.

Since 2004, NASA has been working to return to the Moon. In contrast to the Apollo missions, two key objectives of the current exploration program is to establish significant infrastructure and an outpost. Achieving these objectives will enable long-duration stays and long-distance exploration of the Moon. To do this, robotic systems will be needed to perform tasks which cannot, or should not, be performed by crew alone. In this paper, we summarize our work to develop "utility robots" for lunar surface operations, present results and lessons learned from field testing, and discuss directions for future research.

In this paper, we describe NASA Ames Research Center’s K10 rover as used in the 2006 Coordinated Field Demonstration at Meteor Crater, Arizona. We briefly discuss the control software architecture and describe a high dynamic range imaging system and panoramic display system used for the remote inspection of an EVA crew vehicle.

At NASA Ames Research Center, the Intelligent Robotics Group (IRG) fields the K9 and K10 class rovers. Both use a mobile robot hardware architecture designed for extensibility and reconfigurability that allows for rapid changes in instrumentation and provides a high degree of modularity. Over the past ssveral years, we have worked with instrument developers at NASA centers, universities, and national laboratories to integrate or partially integrate their instruments onboard the K9 and K10 rovers. Early efforts required considerable interaction to work through integration issues such as power, data protocol and mechanical mounting. These interactions informed the design of our current avionics architecture, and have simplified more recent integration projects. In this paper, we will describe the IRG extensible avionics and software architecture and the effect it has had on our recent instrument integration efforts, including integration of four Mars Instrument Development Program devices.

NASA is planning to send humans and robots back to the Moon before 2020. In order for extended missions to be productive, high quality maps of lunar terrain and resources are required. Although orbital images can provide much information, many features (local topography, resources, etc) will have to be characterized directly on the surface. To address this need, we are developing a system to perform site survey and sampling. The system includes multiple robots and humans operating in a variety of team configurations, coordinated via peer-to-peer human-robot interaction. In this paper, we present our system design and describe planned field tests.

In this paper, we present an overview of the CLARAty (coupled layer architecture for robotic autonomy) architecture and describe the growth of capabilities and algorithms now available within this framework. We discuss the challenges of developing a software system with remote institutions and the lessons learned in our experience developing CLARAty with ARC, JPL, and Carnegie Mellon University. We describes the rover testbeds, in particular the K9 rover, and the integration and demonstration of new technologies enabling robust execution, single communication cycle instrument placement, fault diagnosis, and autonomous science.

To command a rover to go to a location of scientific interest on a remote planet, the rover must be capable of reliably tracking the target designated by a scientist from about ten rover lengths away. The rover must maintain lock on the target while traversing rough terrain and avoiding obstacles without the need for communication with Earth. Among the challenges of tracking targets from a rover are the large changes in the appearance and shape of the selected target as the rover approaches it, the limited frame rate at which images can be acquired and processed, and the sudden changes in camera pointing as the rover goes over rocky terrain. We have investigated various techniques for combining 2D and 3D information in order to increase the reliability of visually tracking targets under Mars like conditions. We present the approaches that we have examined on simulated data and tested onboard the Rocky 8 rover in the JPL Mars Yard and the K9 rover in the ARC Marscape. These techniques include results for 2D trackers, ICP, visual odometry, and 2D/3D trackers.

Future Mars rovers, such as the planned 2009 MSL rover, require sufficient autonomy to robustly approach rock targets and place an instrument in contact with them. It took the 1997 Sojourner Mars rover between 3 and 5 communications cycles to accomplish this. This paper describes the NASA Ames approach to robustly accomplishing single cycle instrument deployment, using the K9 prototype Mars rover. An off-board 3D site model is used to select science targets for the rover. K9 navigates to targets using deduced reckoning, and autonomously assesses the target area to determine where to place an arm mounted microscopic camera. Onboard K9 is a resource cognizant conditional executive, which extends the complexity and duration of operations that a can be accomplished without intervention from mission control.

In an ongoing series of field experiments, the Ames Marsokhod rover is deployed to remote locations and operated by scientists in simulated planetary explorations. These experiments provide insight both for scientists preparing for real planetary surface exploration and for robotics researchers. In this paper we will provide an overview of our work with the Marsokhod, describe the various subsystems that have been developed, discuss the latest in a series of field experiments, and discuss the lessons learned about performing remote geology.

Nomad is a mobile robot designed for extended planetary exploration. In June and July of 1997, Nomad performed its first such mission, traversing more than 220 kilometers in the Atacama Desert of Chile and exploring a landscape analogous to that of the Moon and Mars. Nomad’s journey, the Atacama Desert Trek, was an unprecedented demonstration of long-distance, long-duration robotic operation. Guided by operators thousands of kilometers away but telepresent via immersive imagery and interfaces, Nomad operated continuously for 45 days. Science field experiments evaluated exploration strategies and analysis techniques for future terrestrial and planetary missions.

We report here progress on a NASA program to develop fiber optic interferometric sensors for aeroacoustic measurements. As reported earlier, NASA's first fiber-optic microphone was developed and fabricated. Preliminary anechoic chamber tests demonstrated successfully its feasibility as an aeroacoustic sensor. Improved performance of a newly designed sensor head is presented here in terms of frequency response function and noise floor.© (1994) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.

Optical computing research at NASA Ames Research Center seeks to utilize the capability of analog optical processing, involving free-space propagation between components, to produce natural implementations of algorithms requiring large degrees of parallel computation. Potential applications being investigated include robotic vision, planetary lander guidance, aircraft engine exhaust analysis, analysis of remote sensing satellite multispectral images, control of space structures, and autonomous aircraft inspection.

Pattern recognition invariant to image rotations of up to 75 deg, using a single filter, has been demonstrated for binary synthetic discriminant function (BSDF) optical filters, suggesting their use in directed graph-arranged data bases which can be rapidly traversed by means of a filter-plane programmable spatial light modulator (SLM). The filter data base is arranged as a tree structure in which the root node filters are invariant to over 60 deg rotation, while the leaves are 5-deg invariant. Results are presented from experiments with BSDFs designed to recognize in-plane-rotated views of a Space Shuttle Orbiter. Using a magnetooptic SLM that is driven at 350 Hz in the filter plane, orientation identifications requiring less than 30 msec have been achieved after sequencing through only 10 BSDFs.

[1] An experiment illustrating two rovers cooperatively exploring a field site was performed at Black Rock Summit, Nevada, in May 2000. The rovers FIDO and K9 are mechanically identical prototype planetary rovers designed at the Jet Propulsion Laboratory. FIDO carried high-resolution false-color infrared and low-resolution monochrome stereo cameras and an infrared point spectrometer on a mast-mounted pointable platform, a manipulator arm equipped with a color microscopic imager, and a coring drill for sample collection. K9 carried on a mast-mounted pointable platform high-resolution color and low-resolution monochrome stereo cameras, and a Laser Induced Breakdown Spectrometer for standoff elemental analysis. A team located at Jet Propulsion Laboratory commanded the two rovers for 3 days. K9 obtained stereo images of targets, and three-dimensional models were constructed to determine the best locations for FIDO to obtain core samples. A drilling target was selected 1.5 m from the starting position of FIDO. Six command cycles and 2 m of traversing were required for FIDO to reach, drill into, and place an instrument on the target. K9 required 11 command cycles to traverse 60 m and obtain full-coverage stereo images of two rock targets along its route. Virtual reality-based visualization software called Viz provided situational awareness of the environment for both rovers. Commands to K9 were planned using Viz, resulting in improved rover performance. The results show that two rovers can be used synergistically to achieve science goals, but further testing is needed to completely explore the value of two-rover missions.

A terrestrial geologist investigates an area by systematically moving among and inspecting surface features, such as outcrops, boulders, contacts and faults. A planetary geologist must explore remotely and use a robot to approach and image surface features. To date, position-based control has been developed to accomplish this task. This method requires an accurate estimate of the feature position, and frequent update of the robot's position. In practice this is error prone, since it relies on interpolation and continuous integration of data from inertial or odometric sensors or other position determination techniques. The development of vision-based control of robot manipulators suggests an alternative approach for mobile robots. We have developed a vision-based control system that enables our Marsokhod mobile robot to drive autonomously to within sampling distance of a visually designated natural feature. This system utilizes a robust correlation technique based on matching the sign of the difference of the Gaussian of images. We will describe our system and our initial results using it during a field experiment in the Painted Desert of Arizona.

We are studying how "robotic follow-up" can improve future planetary exploration. Robotic follow-up, which we define as augmenting human field work with subsequent robot activity, is a field exploration technique designed to increase human productivity and science return. To better understand the benefits, requirements, limitations and risks associated with this technique, we are conducting analog field tests with human and robot teams at the Haughton Crater impact structure on Devon Island, Canada. In this paper, we discuss the motivation for robotic follow-up, describe the scientific context and system design for our work, and present results and lessons learned from field testing.