Engineering topics

Kulczycki, Eric A.

Publications and source records attributed to Kulczycki, Eric A..

8 records

NASA NTRS2012

360 deg Camera Head for Unmanned Sea Surface Vehicles

The 360 camera head consists of a set of six color cameras arranged in a circular pattern such that their overlapping fields of view give a full 360 view of the immediate surroundings. The cameras are enclosed in a watertight container along with support electronics and a power distribution system. Each camera views the world through a watertight porthole. To prevent overheating or condensation in extreme weather conditions, the watertight container is also equipped with an electrical cooling unit and a pair of internal fans for circulation.

Townsend, Julie A.↗

NASA NTRS2009

A Robust Mechanical Sensing System for Unmanned Sea Surface Vehicles

The need for autonomous navigation and intelligent control of unmanned sea surface vehicles requires a mechanically robust sensing architecture that is watertight, durable, and insensitive to vibration and shock loading. The sensing system developed here comprises four black and white cameras and a single color camera. The cameras are rigidly mounted to a camera bar that can be reconfigured to mount multiple vehicles, and act as both navigational cameras and application cameras. The cameras are housed in watertight casings to protect them and their electronics from moisture and wave splashes. Two of the black and white cameras are positioned to provide lateral vision. They are angled away from the front of the vehicle at horizontal angles to provide ideal fields of view for mapping and autonomous navigation. The other two black and white cameras are positioned at an angle into the color camera's field of view to support vehicle applications. These two cameras provide an overlap, as well as a backup to the front camera. The color camera is positioned directly in the middle of the bar, aimed straight ahead. This system is applicable to any sea-going vehicle, both on Earth and in space.

Kulczycki, Eric A.↗

NASA NTRS2009

Mars Balloon Flight Test Results

This paper describes a set of four Earth atmosphere flight test experiments on prototype helium superpressure balloons designed for Mars. Three of the experiments explored the problem of aerial deployment and inflation, using the cold, low density environment of the Earth's stratosphere at an altitude of 30-32 km as a proxy for the Martian atmosphere. Auxiliary carrier balloons were used in three of these test flights to lift the Mars balloon prototype and its supporting system from the ground to the stratosphere where the experiment was conducted. In each case, deployment and helium inflation was initiated after starting a parachute descent of the payload at 5 Pa dynamic pressure, thereby mimicking the conditions expected at Mars after atmospheric entry and high speed parachute deceleration. Upward and downward looking video cameras provided real time images from the flights, with additional data provided by onboard temperature, pressure and GPS sensors. One test of a 660 cc pumpkin balloon was highly successful, achieving deployment, inflation and separation of the balloon from the flight train at the end of inflation; however, some damage was incurred on the balloon during this process. Two flight tests of 12 m diameter spherical Mylar balloons were not successful, although some lessons were learned based on the failure analyses. The final flight experiment consisted of a ground-launched 12 m diameter spherical Mylar balloon that ascended to the designed 30.3 km altitude and successfully floated for 9.5 hours through full noontime daylight and into darkness, after which the telemetry system ran out of electrical power and tracking was lost. The altitude excursions for this last flight were +/-75 m peak to peak, indicating that the balloon was essentially leak free and functioning correctly. This provides substantial confidence that this balloon design will fly for days or weeks at Mars if it can be deployed and inflated without damage.

deployment↗

NASA NTRS2009

Aerobot Autonomy Architecture

An architecture for autonomous operation of an aerobot (i.e., a robotic blimp) to be used in scientific exploration of planets and moons in the Solar system with an atmosphere (such as Titan and Venus) is undergoing development. This architecture is also applicable to autonomous airships that could be flown in the terrestrial atmosphere for scientific exploration, military reconnaissance and surveillance, and as radio-communication relay stations in disaster areas. The architecture was conceived to satisfy requirements to perform the following functions: a) Vehicle safing, that is, ensuring the integrity of the aerobot during its entire mission, including during extended communication blackouts. b) Accurate and robust autonomous flight control during operation in diverse modes, including launch, deployment of scientific instruments, long traverses, hovering or station-keeping, and maneuvers for touch-and-go surface sampling. c) Mapping and self-localization in the absence of a global positioning system. d) Advanced recognition of hazards and targets in conjunction with tracking of, and visual servoing toward, targets, all to enable the aerobot to detect and avoid atmospheric and topographic hazards and to identify, home in on, and hover over predefined terrain features or other targets of scientific interest. The architecture is an integrated combination of systems for accurate and robust vehicle and flight trajectory control; estimation of the state of the aerobot; perception-based detection and avoidance of hazards; monitoring of the integrity and functionality ("health") of the aerobot; reflexive safing actions; multi-modal localization and mapping; autonomous planning and execution of scientific observations; and long-range planning and monitoring of the mission of the aerobot. The prototype JPL aerobot (see figure) has been tested extensively in various areas in the California Mojave desert.

Elfes, Alberto↗

NASA NTRS2008

On the Development of Parameterized Linear Analytical Longitudinal Airship Models

In order to explore Titan, a moon of Saturn, airships must be able to traverse the atmosphere autonomously. To achieve this, an accurate model and accurate control of the vehicle must be developed so that it is understood how the airship will react to specific sets of control inputs. This paper explains how longitudinal aircraft stability derivatives can be used with airship parameters to create a linear model of the airship solely by combining geometric and aerodynamic airship data. This method does not require system identification of the vehicle. All of the required data can be derived from computational fluid dynamics and wind tunnel testing. This alternate method of developing dynamic airship models will reduce time and cost. Results are compared to other stable airship dynamic models to validate the methods. Future work will address a lateral airship model using the same methods.

aerobot↗

NASA NTRS2008

An Autonomy Architecture for Aerobot Exploration of the Saturnian Moon Titan

The Huygens probe arrived at Saturn's moon Titan on January 14, 2005, unveiling a world that is radically different from any other in the Solar system. The data obtained, complemented by continuing observations from the Cassini spacecraft, show methane lakes, river channels and drainage basins, sand dunes, cryovolcanos and sierras. This has lead to an enormous scientific interest in a follow-up mission to Titan, using a robotic lighter-than-air vehicle (or aerobot). Aerobots have modest power requirements, can fly missions with extended durations, and have very long distance traverse capabilities. They can execute regional surveys, transport and deploy scientific instruments and in-situ laboratory facilities over vast distances, and also provide surface sampling at strategic science sites. This paper describes our progress in the development of the autonomy technologies that will be required for exploration of Titan. We provide an overview of the autonomy architecture and some of its key components. We also show results obtained from autonomous flight tests conducted in the Mojave desert.

Titan↗

NASA NTRS2008

The Telesupervised Adaptive Ocean Sensor Fleet (TAOSF) Architecture: Coordination of Multiple Oceanic Robot Boats

Earth science research must bridge the gap between the atmosphere and the ocean to foster understanding of Earth s climate and ecology. Ocean sensing is typically done with satellites, buoys, and crewed research ships. The limitations of these systems include the fact that satellites are often blocked by cloud cover, and buoys and ships have spatial coverage limitations. This paper describes a multi-robot science exploration software architecture and system called the Telesupervised Adaptive Ocean Sensor Fleet (TAOSF). TAOSF supervises and coordinates a group of robotic boats, the OASIS platforms, to enable in-situ study of phenomena in the ocean/atmosphere interface, as well as on the ocean surface and sub-surface. The OASIS platforms are extended deployment autonomous ocean surface vehicles, whose development is funded separately by the National Oceanic and Atmospheric Administration (NOAA). TAOSF allows a human operator to effectively supervise and coordinate multiple robotic assets using a sliding autonomy control architecture, where the operating mode of the vessels ranges from autonomous control to teleoperated human control. TAOSF increases data-gathering effectiveness and science return while reducing demands on scientists for robotic asset tasking, control, and monitoring. The first field application chosen for TAOSF is the characterization of Harmful Algal Blooms (HABs). We discuss the overall TAOSF architecture, describe field tests conducted under controlled conditions using rhodamine dye as a HAB simulant, present initial results from these tests, and outline the next steps in the development of TAOSF.

sensor web↗

NASA NTRS2007

Trajectory Generation and Path Planning for Autonomous Aerobots

This paper presents global path planning algorithms for the Titan aerobot based on user defined waypoints in 2D and 3D space. The algorithms were implemented using information obtained through a planner user interface. The trajectory planning algorithms were designed to accurately represent the aerobot's characteristics, such as minimum turning radius. Additionally, trajectory planning techniques were implemented to allow for surveying of a planar area based solely on camera fields of view, airship altitude, and the location of the planar area's perimeter. The developed paths allow for planar navigation and three-dimensional path planning. These calculated trajectories are optimized to produce the shortest possible path while still remaining within realistic bounds of airship dynamics.

trajectory↗