Mike Rasay

The O/OREOS Mission: First Science Data from the Space Environment Viability of Organics (SEVO) Payload

We report the first science results from the Space Environment Viability of Organics (SEVO) payload aboard the Organism/Organic Exposure to Orbital Stresses (O/OREOS) free-flying nanosatellite, which completed its nominal spaceflight mission in May 2011 but continues to acquire data biweekly. The SEVO payload integrates a compact UV-visible-NIR spectrometer, utilizing the Sun as its light source, with a 24-cell sample carousel that houses four classes of vacuum-deposited organic thin films: polycyclic aromatic hydrocarbon (PAH), amino acid, metalloporphyrin, and quinone. The organic films are enclosed in hermetically sealed sample cells that contain one of four astrobiologically relevant microenvironments. Results are reported in this paper for the first 309 days of the mission, during which the samples were exposed for ∼2210 h to direct solar illumination (∼1080 kJ/cm(2) of solar energy over the 124-2600 nm range). Transmission spectra (200-1000 nm) were recorded for each film, at first daily and subsequently every 15 days, along with a solar spectrum and the dark response of the detector array. Results presented here include eight preflight and 16 in-flight spectra of eight SEVO sample cells. Spectra from the PAH thin film in a water-vapor-containing microenvironment indicate measurable change due to solar irradiation in orbit, while three other nominally water-free microenvironments show no appreciable change. The quinone anthrarufin showed high photostability and no significant spectroscopically measurable change in any of the four microenvironments during the same period. The SEVO experiment provides the first in situ real-time analysis of the photostability of organic compounds and biomarkers in orbit.

Responsive Small Satellite Mission Operations Using An Enterprise-Class Internet-Based Command and Control Network

Rapid integration of spacecraft into low-cost mission control systems is an essential element of enabling cost-effective, responsive space missions. This paper describes a distributed satellite ground segment and control network that is developed and operated by students at Santa Clara University in order to support a wide variety of NASA and university-class small spacecraft. In addition to reviewing the technical design of the system and summarizing the missions being supported, the paper outlines several strategies for implementing a low-cost system that supports rapid integration of new spacecraft.

An underwater robotic testbed for multi-vehicle control

The PVC-ROV underwater robot testbed is a low-cost, three vehicle system designed to support research into multi-robot control techniques. Each vehicle is composed of a PVC frame with bilge-pump motors, a central microcontroller, and hobby-class sensing and power components. In addition, each vehicle is tethered to a surface buoy by a 15 meter tether and wirelessly exchanges data with an off-board, Matlab-based control program; an acoustic tracking system simultaneously tracks the position of each vehicle. Use of the testbed has begun with demonstration of two-vehicle cluster space control, a specific control technique developed by researchers in Santa Clara Universitys Robotic Systems Laboratory. This paper reviews the design of the PVC-ROV testbed and presents initial results in using the testbed to demonstrate the cluster control technique in an underwater environment.

A Multi-Robot Testbed for Adaptive Sampling Experimentation via Radio Frequency Fields

Adaptive navigation is the process by which a vehicle determines where to go based on information received while moving through the field of interest. Adaptive sampling is a specific form of this in which that information is environmental data sampled by the robot. This may be beneficial in order to save time/energy compared to a conventional navigation strategy in which the entire field is traversed. Our work in this area focuses on multi-robot gradient-based techniques for the adaptive sampling of a scalar field. To date, we have experimentally demonstrated multi-robot gradient ascent/descent as well as contour following using automated marine surface vessels. In simulation we have verified controllers for ridge descent / valley ascent as well as saddle point detection and loitering. To support rapid development of our controllers, we have developed a new testbed using wireless transmitters to establish a simple, large-scale, customizable scalar field based on the strength of the radio frequency field. A cluster of six land rovers equipped with radio signal strength sensors is then used to process sampled data, to make adaptive decisions on how to move, and to execute those moves. In this paper, we describe the technical design of the testbed, present initial experimental results, and describe our ongoing research and development work in the area of adaptive sampling and multi-robot control.Copyright