Development and Testing of Advanced Pressure Suit Technologies and Analogues for Earth-Based Simulations
Massimiliano Di Capua, David L. Akin, K. Davis
- Year
- 2011
- Citations
- 7
Abstract
The University of Maryland (UMd), along with Arizona State University (ASU), initiated a research e ort in August 2010 under the support of the NASA Lunar Advanced Science and Exploration Research (LASER) program. In order to ful ll the objectives of this grant, the UMd Space Systems Laboratory (SSL) Human Systems team has been continuing its on-going development of advanced controls and displays for planetary surface EVA. In addition to advanced avionics, two space suit simulators have been designed and built with the purpose of serving as test beds to aid the evaluation of human-robot cooperative surface operations, as well as providing novel additional capabilities to the suited astronaut. The space suit simulators, dubbed MX-A (Alpha) and MX-B (Bravo), attempt to emulate the constraints typical of a pressurized suit in an unpressurized environment. By reducing the system complexity, support equipment overhead, and required operating protocols, we are able to open access to a wider range of test subjects; this allows faster, more accessible, and more conclusive experimental procedures. In this paper we will describe in detail the design and assembly process of these two suit simulators, with speci c focus on avionics and advanced controls and displays. Field tests under this program focus on the use of the suit simulators and an astronaut support rover previously built in collaboration between UMd and ASU. For the current test cycle, several rover control interfaces were prototyped and tested, including speech recognition and synthesis, head tracking, gestural control, and suit-integrated joystick teleoperation. This paper documents the experimental evaluation process adopted in this study to compare all the above interfaces, and presents experimental results and conclusions.
Keywords
Related papers
Statistical Learning Theory
Yuhai Wu, Vladimir Vapnik
1999
Artificial intelligence: a modern approach
1995
Applied Nonlinear Control
Jean-Jacques Slotine, Weiping Li
1991
A new optimizer using particle swarm theory
R.C. Eberhart, James Kennedy
2002