Michael D. Wagner

An autonomous spacecraft agent prototype

This paper describes the New Millennium Remote Agent (NMRA) architecture for autonomous spacecraft control systems. The architecture supports challenging requirements of the autonomous spacecraft domain not usually addressed in mobile robot architectures, including highly reliable autonomous operations over extended time periods in the presence of tight resource constraints, hard deadlines, limited observability, and concurrent activity. A hybrid architecture, NMRA integrates traditional real-time monitoring and control with heterogeneous components for constraint-based planning and scheduling, robust multi-threaded execution, and model-based diagnosis and reconfiguration. Novel features of this integrated architecture include support for robust closed-loop generation and execution of concurrent temporal plans and a hybrid procedural/deductive executive.

First Experiments in the Robotic Investigation of Life in the Atacama Desert of Chile

The Atacama Desert of northern Chile may be the most lifeless place on Earth, yet where the desert meets the Pacific coastal range desiccation-tolerant micro-organisms are known to exist. The gradient of biodiversity and habitats in the Atacama’s subregions remain unexplored and are the focus of the Life in the Atacama project. To conduct this investigation, long traverses must be made across the desert with instruments for geologic and biologic measurements. In this paper we motivate the Life in the Atacama project from both astrobiologic and robotic perspectives. We focus on some of the research challenges we are facing to enable endurance navigation, resource cognizance, and long-term survivability. We conducted our first scientific investigation and technical experiments in Chile with the mobile robot Hyperion. We describe the experiments and the results of our analysis. These results give us insight into the design of an effective robotic astrobiologist and into the methods by which we will conduct scientific investigation in the next field season.

Technology and Field Demonstration of Robotic Search for Antarctic Meteorites

Meteorites are the only significant source of material from other planets and asteroids, and therefore are of immense scientific value. Antarctica’s frozen and pristine environment has proven to be the best place on earth to harvest meteorite specimens. The lack of melting and surface erosion keep meteorite falls visible on the ice surface in pristine condition for thousands of years. In this article, we describe the robotic technologies and field demonstration that enabled the first discovery of Antarctic meteorites by a robot. Using a novel autonomous control architecture, specialized science sensing, combined manipulation and visual servoing, and Bayesian classification, the Nomad robot found and classified five indigenous meteorites during an expedition to the remote site of Elephant Moraine in January 2000. This article first overviews Nomad’s mechatronic systems and details the control architecture that governs the robot’s autonomy and classifier that enables the autonomous interpretation of scientific data. It then focuses on the technical results achieved during field demonstrations at Elephant Moraine. Finally, the article discusses the benefits and limitations of robotic autonomy in science missions. Science autonomy is shown as a capable and expandable architecture for exploration and in situ classification. Inefficiencies in the existing implementation are explained with a focus on important lessons that outline future work.

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.

Challenges in Autonomous Vehicle Testing and Validation

Software testing is all too often simply a bug hunt rather than a wellconsidered exercise in ensuring quality. A more methodical approach than a simple cycle of system-level test-fail-patch-test will be required to deploy safe autonomous vehicles at scale. The ISO 26262 development V process sets up a framework that ties each type of testing to a corresponding design or requirement document, but presents challenges when adapted to deal with the sorts of novel testing problems that face autonomous vehicles. This paper identifies five major challenge areas in testing according to the V model for autonomous vehicles: driver out of the loop, complex requirements, non-deterministic algorithms, inductive learning algorithms, and failoperational systems. General solution approaches that seem promising across these different challenge areas include: phased deployment using successively relaxed operational scenarios, use of a monitor/actuator pair architecture to separate the most complex autonomy functions from simpler safety functions, and fault injection as a way to perform more efficient edge case testing. While significant challenges remain in safety-certifying the type of algorithms that provide high-level autonomy themselves, it seems within reach to instead architect the system and its accompanying design process to be able to employ existing software safety approaches.

CHIMP, the CMU Highly Intelligent Mobile Platform

We have developed the CHIMP CMU Highly Intelligent Mobile Platform robot as a platform for executing complex tasks in dangerous, degraded, human-engineered environments. CHIMP has a near-human form factor, work-envelope, strength, and dexterity to work effectively in these environments. It avoids the need for complex control by maintaining static rather than dynamic stability. Utilizing various sensors embedded in the robots head, CHIMP generates full three-dimensional representations of its environment and transmits these models to a human operator to achieve latency-free situational awareness. This awareness is used to visualize the robot within its environment and preview candidate free-space motions. Operators using CHIMP are able to select between task, workspace, and joint space control modes to trade between speed and generality. Thus, they are able to perform remote tasks quickly, confidently, and reliably, due to the overall design of the robot and software. CHIMPs hardware was designed, built, and tested over 15i¾?months leading up to the DARPA Robotics Challenge. The software was developed in parallel using surrogate hardware and simulation tools. Over a six-week span prior to the DRC Trials, the software was ported to the robot, the system was debugged, and the tasks were practiced continuously. Given the aggressive schedule leading to the DRC Trials, development of CHIMP focused primarily on manipulation tasks. Nonetheless, our team finished 3rd out of 16. With an upcoming year to develop new software for CHIMP, we look forward to improving the robots capability and increasing its speed to compete in the DRC Finals.

The Science Autonomy System of the Nomad robot

The Science Autonomy System (SAS) is a hierarchical control architecture for exploration and in situ science that integrates sensing, navigation, classification and mission planning. The Nomad robot demonstrated the capabilities of the SAS during a January 2000 expedition to Elephant Moraine, Antarctica where it accomplished the first meteorite discoveries made by a robot. In the paper, the structure and functionality of the three-tiered SAS are detailed. Results and lessons learned are presented with a focus on important future research.

Robotic Antarctic meteorite search: outcomes

Automation of the search for and classification of Antarctic meteorites offers a unique case for early demonstration of robotics in a scenario analogous to geological exploratory missions to other planets and to the Earths extremes. Moreover, the discovery of new meteorite samples is of great value because meteorites are the only significant source of extraterrestrial material available to scientists. In this paper we focus on the primary outcomes and technical lessons learned from the first field demonstration of autonomous search and in situ classification of Antarctic meteorites by a robot. Using a novel autonomous control architecture, specialized science sensing, combined manipulation and visual servoing, and Bayesian classification, the Nomad robot classified five indigenous meteorites during an expedition to the remote site of Elephant Moraine in January 2000. Nomads expedition proved the rudiments of science autonomy and exemplified the merits of machine learning techniques for autonomous geological classification in real-world settings. On the other hand, the expedition showcased the difficulty in executing reliable robotic deployment of science sensors and a limited performance in the speed and coverage of autonomous search.

Sun-Synchronous Robotic Exploration: Technical Description and Field Experimentation

Sun-synchronous robotic exploration is accomplished by reasoning about sunlight: where the Sun is in the sky, where and when shadows will fall, and how much power can be obtained through various courses of action. We conducted experiments in the Canadian high arctic using a solar-powered rover to prove the concept of Sun-synchronous exploration. Using knowledge of orbital mechanics, local terrain, and locomotion power, the rover Hyperion planned Sun-synchronous routes to visit designated sites while obtaining the necessary solar power for continuous operation. Hyperion executed its plan, beginning and ending each 24-h period with batteries fully charged, after traveling two circuits of more than 6 km in barren, Mars-like terrain. The objective of the Sun-Synchronous Navigation project (http://www.frc.ri.cmu.edu/sunsync) was to create hardware and software technologies needed to realize Sun-synchronous exploration and to validate these technologies in field experimentation. In the process, we learned important technical lessons regarding rover mechanism, motion control, planning algorithms, and system architecture. In this paper we describe the concept of Sun-synchronous exploration. We overview the design of the robot Hyperion and the software system that enables it to operate in synchrony with the Sun. We then discuss results and lessons from analysis of our field experiments. This paper describes rover and planetary exploration research at Carnegie Mellon during 2000-2002.

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.