The Trajectory Synthesizer Generalized Profile Interface

The Trajectory Synthesizer is a software program that generates aircraft predictions for Air Traffic Management decision support tools. The Trajectory Synthesizer being used by researchers at NASA Ames Research Center was restricted in the number of trajectory types that could be generated. This limitation was not sufficient to support the rapidly changing Air Traffic Management research requirements. The Generalized Profile Interface was developed to address this issue. It provides a flexible approach to describe the constraints applied to trajectory generation and may provide a method for interoperability between trajectory generators. It also supports the request and generation of new types of trajectory profiles not possible with the previous interface to the Trajectory Synthesizer. Other enhancements allow the Trajectory Synthesizer to meet the current and future needs of Air Traffic Management research

Surface Telerobotics: Development and Testing of a Crew Controlled Planetary Rover System

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

Structured Light-Based Hazard Detection For Planetary Surface Navigation

This paper describes a structured light-based sensor for hazard avoidance in planetary environments. The system presented here can also be used in terrestrial applications constrained by reduced onboard power and computational complexity and low illumination conditions. The sensor is on a calibrated camera and laser dot projector system. The onboard hazard avoidance system determines the position of the projected dots in the image and through a triangulation process detects potential hazards. The paper presents the design parameters for this sensor and describes the image based solution for hazard avoidance. The system presented here was tested extensively in day and night conditions in Lunar analogue environments. The current system achieves over 97 detection rate with 1.7 false alarms over 2000 images

Tele-Operated Lunar Rover Navigation Using Lidar

Near real-time tele-operated driving on the lunar surface remains constrained by bandwidth and signal latency despite the Moon s relative proximity. As part of our work within NASA s Human-Robotic Systems Project (HRS), we have developed a stand-alone modular LIDAR based safeguarded tele-operation system of hardware, middleware, navigation software and user interface. The system has been installed and tested on two distinct NASA rovers-JSC s Centaur2 lunar rover prototype and ARC s KRex research rover- and tested over several kilometers of tele-operated driving at average sustained speeds of 0.15 - 0.25 m/s around rocks, slopes and simulated lunar craters using a deliberately constrained telemetry link. The navigation system builds onboard terrain and hazard maps, returning highest priority sections to the off-board operator as permitted by bandwidth availability. It also analyzes hazard maps onboard and can stop the vehicle prior to contacting hazards. It is robust to severe pose errors and uses a novel scan alignment algorithm to compensate for attitude and elevation errors

Field Testing of Utility Robots for Lunar Surface Operations

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

Challenges of Rover Navigation at the Lunar Poles

Observations from Lunar Prospector, LCROSS, Lunar Reconnaissance Orbiter (LRO), and other missions have contributed evidence that water and other volatiles exist at the lunar poles in permanently shadowed regions. Combining a surface rover and a volatile prospecting and analysis payload would enable the detection and characterization of volatiles in terms of nature, abundance, and distribution. This knowledge could have impact on planetary science, in-situ resource utilization, and human exploration of space. While Lunar equatorial regions of the Moon have been explored by manned (Apollo) and robotic missions (Lunokhod, Cheng'e), no surface mission has reached the lunar poles

Robotic Follow-Up for Human Exploration

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

Urban Area Unmanned Aerial Systems Sensor Capabilities for Ensuring Ground Hazards Safety

Unmanned aerial systems (UASs) in urban areas can pose significant safety risks to dynamic ground objects (DGOs) such as people, pets, and bikes; especially for off-nominal emergency traverses and landings. This paper will examine a framework for evaluating the UAS safety benefits which can be achieved by classifying DGO hazards, modeling their behavior, and assigning collision costs. DGOs are assumed to be any ground objects which are either moving or capable of moving. Safety benefits will be assessed by analyzing metrics computed from UAS and DGO trajectories which take into account intent and uncertainties. This paper will establish the theoretical relationships mapping these trajectories and DGO classifications to safety levels. Sensor capabilities will be mapped to DGO trajectory uncertainties, so that safety can be directly estimated from the sensor specifications for a given UAS trajectory

Robotic Site Survey at Haughton Crater

In Summer 2007, we field-tested a robotic survey system at Haughton Crater (Devon Island, Canada). Two NASA Ames K10 planetary rovers performed systematic surveys of several simulated lunar sites, including a roughly 700m x 700m region called Drill Hill. The rovers carried a 3D scanning lidar for topographic mapping and ground penetrating radar to map subsurface structure. In this paper, we describe our robotic survey system, present the results of the field test, and summarize the lessons learned. 1