Engineering topics
Publications and source records attributed to Deans, Matt.
This presentation is an overview of the Integrated System for Autonomous and Adaptive Caretaking (ISAAC) project, funded by the STMD Game Changing Development program to develop autonomous caretaking capabilities for future human exploration spacecraft, especially during uncrewed phases.
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.
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.
A visual-tracker computer program controls an articulated mast on a Mars rover to keep a designated feature (a target) in view while the rover drives toward the target, avoiding obstacles. Several prior visual-tracker programs have been tested on rover platforms; most require very small and well-estimated motion between consecutive image frames a requirement that is not realistic for a rover on rough terrain. The present visual-tracker program is designed to handle large image motions that lead to significant changes in feature geometry and photometry between frames. When a point is selected in one of the images acquired from stereoscopic cameras on the mast, a stereo triangulation algorithm computes a three-dimensional (3D) location for the target. As the rover moves, its body-mounted cameras feed images to a visual-odometry algorithm, which tracks two-dimensional (2D) corner features and computes their old and new 3D locations. The algorithm rejects points, the 3D motions of which are inconsistent with a rigid-world constraint, and then computes the apparent change in the rover pose (i.e., translation and rotation). The mast pan and tilt angles needed to keep the target centered in the field-of-view of the cameras (thereby minimizing the area over which the 2D-tracking algorithm must operate) are computed from the estimated change in the rover pose, the 3D position of the target feature, and a model of kinematics of the mast. If the motion between the consecutive frames is still large (i.e., 3D tracking was unsuccessful), an adaptive view-based matching technique is applied to the new image. This technique uses correlation-based template matching, in which a feature template is scaled by the ratio between the depth in the original template and the depth of pixels in the new image. This is repeated over the entire search window and the best correlation results indicate the appropriate match. The program could be a core for building application programs for systems that require coordination of vision and robotic motion.
To command a rover to go to a location of scientific interest on a remote planet, the rover must be capable of reliably tracking the target designated by the scientist from ten or more meters away. The rover must maintain lock on the target while traversing rough terrain and avoiding obstacles without the need for communication with Earth.