Trey Smith

First Results in the Coordination of Heterogeneous Robots for Large-Scale Assembly

While many multi-robot systems rely on fortuitous cooperation between agents, some tasks, such as the assembly of large structures, require tighter coordination. We present a general software architecture for coordinating heterogeneous robots that allows for both autonomy of the individual agents as well as explicit coordination. This paper presents recent results with three robots with very different configurations. Working as a team, these robots are able to perform a high-precision docking task that none could achieve individually.

Autonomous rovers for Mars exploration

The Pathfinder mission demonstrated the potential for robotic Mars exploration but at the same time indicated the need for more robust rover autonomy. Future planned missions call for long traverses over unknown terrain, robust navigation and instrument placement, and reliable operations for extended periods of time. Ultimately, missions may visit multiple science sites in a single day and perform opportunistic science data collection, as well as complex scouting, construction, and maintenance tasks in preparation for an eventual human presence. Significant advances in robust autonomous operations are needed to enable these types of missions. Towards this end, we have designed an on-board executive architecture that incorporates robust flexible operation, resource utilization, and failure recovery. In addition, we have designed ground tools to produce and refine contingent schedules that take advantage of the on-board architectures flexible execution characteristics. Together, the on-board executive and the ground tools constitute an integrated rover autonomy architecture.

A Layered Architecture for Coordination of Mobile Robots

This paper presents an architecture that enables multiple robots to explicitly coordinate actions at multiple levels of abstraction. In particular, we are developing an extension to the traditional three-layered robot architecture that enables robots to interact directly at each layer — at the behavioral level, the robots create distributed control loops; at the executive level, they synchronize task execution; at the planning level, they use market-based techniques to assign tasks, form teams, and allocate resources. We illustrate these ideas through applications in multi-robot assembly, multi-robot deployment, and multi-robot mapping.

Life in the Atacama: Searching for life with rovers (science overview)

[1] The Life in the Atacama project investigated the regional distribution of life and habitats in the Atacama Desert of Chile. We sought to create biogeologic maps through survey traverses across the desert using a rover carrying biologic and geologic instruments. Elements of our science approach were to: Perform ecological transects from the relatively wet coastal range to the arid core of the desert; use converging evidence from science instruments to reach conclusions about microbial abundance; and develop and test exploration strategies adapted to the search of scattered surface and shallow subsurface microbial oases. Understanding the ability of science teams to detect and characterize microbial life signatures remotely using a rover became central to the project. Traverses were accomplished using an autonomous rover in a method that is technologically relevant to Mars exploration. We present an overview of the results of the 2003, 2004, and 2005 field investigations. They include: The confirmed identification of microbial habitats in daylight by detecting fluorescence signals from chlorophyll and dye probes; the characterization of geology by imaging and spectral measurement; the mapping of life along transects; the characterization of environmental conditions; the development of mapping techniques including homogeneous biological scoring and predictive models of habitat location; the development of exploration strategies adapted to the search for life with an autonomous rover capable of up to 10 km of daily traverse; and the autonomous detection of life by the rover as it interprets observations on-the-fly and decides which targets to pursue with further analysis.

Automatic detection and classification of features of geologic interest

The volume of data that planetary rovers and their instrument payloads can produce will continue to outpace available deep space communication bandwidth. Future exploration rovers will require science autonomy systems that interpret collected data in order to selectively compress observations, summarize results, and respond to new discoveries. We present a method that uses a probabilistic fusion of data from multiple sensor sources for onboard segmentation, detection and classification of geological properties. Field experiments performed in the Atacama desert in Chile show the systems performance versus ground truth on the specific problem of automatic rock identification.

Robotic ecological mapping: Habitats and the search for life in the Atacama Desert

[1] As part of the three-year ‘Life in the Atacama’ (LITA) project, plant and microbial abundance were mapped within three sites in the Atacama Desert, Chile, using an automated robotic rover. On-board fluorescence imaging of six biological signatures (e.g., chlorophyll, DNA, proteins) was used to assess abundance, based on a percent positive sample rating system and standardized robotic ecological transects. The percent positive rating system scored each sample based on the measured signal strength (0 for no signal to 2 for strong signal) for each biological signature relative to the total rating possible. The 2005 field experiment results show that percent positive ratings varied significantly across Site D (coastal site with fog), with patchy zones of high abundance correlated with orbital and microscale habitat types (heaved surface crust and gravel bars); alluvial fan habitats generally had lower abundance. Non-random multi-scale biological patchiness also characterized interior desert Sites E and F, with relatively high abundance associated with (paleo)aqueous habitats such as playas. Localized variables, including topography, played an important, albeit complex, role in microbial spatial distribution. Site D biosignature trends correlated with culturable soil bacteria, with MPN ranging from 10-1000 CFU/g-soil, and chlorophyll ratings accurately mapped lichen/moss abundance (Site D) and higher plant (Site F) distributions. Climate also affected biological patchiness, with significant correlation shown between abundance and (rover) air relative humidity, while lichen patterns were linked to the presence of fog. Rover biological mapping results across sites parallel longitudinal W-E wet/dry/wet Atacama climate trends. Overall, the study highlights the success of targeting of aqueousassociated habitats identifiable from orbital geology and mineralogy. The LITA experience also suggests the terrestrial study of life and its distribution, particularly the fields of landscape ecology and ecohydrology, hold critical lessons for the search for life on other planets. Their applications to robotic sampling strategies on Mars should be further exploited.

Application of pulsed‐excitation fluorescence imager for daylight detection of sparse life in tests in the Atacama Desert

A daylight fluorescence imager was deployed on an autonomous rover, Zoe, to detect life on the surface and shallow subsurface in regions of the Atacama Desert in Chile during field tests between 2003 and 2005. In situ fluorescent measurements were acquired from naturally fluorescing biomolecules such as chlorophyll and from specific fluorescent probes sprayed on the samples, targeting each of the four biological macromolecule classes: DNA, protein, lipid, and carbohydrate. RGB context images were also acquired. Preparatory reagents were applied to enhance the dye probe penetration and fluorescence intensity of chlorophyll. Fluorescence imager data sets from 257 samples were returned to the Life in the Atacama science team. A variety of visible life forms, such as lichens, were detected, and several of the dye probes produced signals from nonphotosynthetic microorganisms.

Information-optimal selective data return for autonomous rover traverse science and survey

Selective data return leverages onboard data analysis to allocate limited bandwidth resources during remote exploration. Here we present an adaptive method to subsample image sequences for downlink. We treat selective data return as a compression problem in which the explorer agent transmits the subset of measurements that are most informative with respect to the complete dataset. Experiments demonstrate selective downlink of navigation imagery by a rover during autonomous geologic investigations in the Atacama desert of Chile. Here automatic analysis identifies informative images using classifications based on natural image statistics. Image texture analysis, together with a context-sensitive Hidden Markov Model representation, permits adaptive downlink in response to geologic unit boundaries. Selective data return improves the science content of returned data for this geologic mapping task.

Astrobee: Developing a Free Flying Robot for the International Space Station

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 Internation Space Station (ISS). This paper will describe the Astrobee project objectives, initial design, concept of operations, and key challenges.

Concepts for science autonomy during robotic traverse and survey

Future Mars rovers will have the ability to autonomously navigate for distances of kilometers. In one sol a traverse may take a rover into unexplored areas beyond its local horizon. Naturally, scientists cannot specify particular targets for the rover in an area they have not yet seen. This paper analyzes what they can specify: priorities that provide the rover with enough information to autonomously select science targets using its onboard sensing. Several autonomous science operational modes and priority types are discussed. We also introduce a science priority language. A team of scientists was asked to use the language in specifying targets for a teleoperated rover, and qualitative results are reported.