The International Space Station (ISS) provides a unique opportunity to capture and quantify the architectural layout and 3-D space utilization in a microgravity environment from the astronauts living and working there. Information gathered will provide critical insight on the minimum net habitable volume (NHV) required for future spacecraft, as well as architectural layout and task designs and efficiencies. This project aims to develop a small, unobtrusive wearable kinematic system to estimate a crewmember’s navigation state vector – position and orientation – as a function of time during the course of their normal daily activities. The proposed device will not require any special infrastructure, and includes completely passive vision and inertial sensors to bound long-term drift in position and orientation estimates, thus providing a location service within the ISS that can integrate with astronauts or moveable equipment. In this project year, we have made significant progress in the definition of the system architecture, concept of operations (CONOPS), data processing pipeline, the development and integration of an algorithm to enable self-initialization and periodically correct accumulated drift through loop closures. Additionally, we have prototype a self-contained portable system for technology demonstration and algorithmic testing in a variety of representative environments.
With the goal of providing ISS astronaut navigation state vector information that can both be visualized by engineers and used in net habitable volume (NHV) modeling and analysis efforts, we have drafted a CONOPS for the use of the system. This CONOPS takes into account the required interactions by the astronauts as well as the required hardware and software functions to complete the required activities. This has subsequently resulted in the definition of key system and functional requirements that will be used to guide the development of an eventual wearable kinematic system. Additionally, we have worked with collaborators at Johnson Space Center (JSC) who support flight integration of technologies to understand the constraints of the ISS operational environment, as well as with our consultant (who is a former ISS crewmember) to ensure the design and operations will be accepted by the crew. Our team has been in collaboration with the JSC Wearables Lab to identify potential collaboration opportunities, such as integration with their wearable carbon dioxide (CO2) system to provide append a location estimate with each measurement.
The principal output of the wearable kinematic system is a time-stamped estimate of the astronaut’s navigation state vector (e.g., position and orientation) when the device is attached to their body. Through discussions with our NASA Space Human Factors and Habitability partners, we identified required performance metrics of the system (e.g., navigation accuracy) that will enable the definition and validation of ongoing net habitable volume modeling efforts. The specification of these performance metrics enabled the definition of a set of criteria to measure navigation performance against when testing a Draper-developed vision-inertial navigation system in the ground-based analog environments.
In our first year, we used a self-contained set of trade study hardware that was previously developed for the U.S. Army, which simultaneously recorded time synchronized data from two cameras and three inertial measurement units (IMUs), was used during various waking routes within the Human Exploration Research Analog (HERA) and the International Space Station (ISS) mockup facility at the NASA Johnson Space Center. The data from a walking route within the ISS mockups and analyzed using Draper Laboratory’s Multi-State Constrained Kalman Filter (“Mischief”) for visual-inertial odometry can be seen on YouTube here: https://www.youtube.com/watch?v=Mb8x4WeM6q8
. In project year 2, we analyzed that same data set using our next-generation algorithm, smoothing and mapping with inertial state estimation (SAMWISE) and were able to repeat the performance, and in many cases show that we had less final position error as a percentage of the estimated route distance. SAMWISE will be the baseline algorithm going forward to enable online initialization and periodic accumulated drift correction using “loop closures.”
Project plans for the upcoming year of the program are to continue the development of the concept of operations and specification of the requirements of the system to enable both the science objectives of modeling and analysis of net habitable volume (NHV) as well as ensuring crew acceptance and use of the device during ISS expeditions. We are continuing our development of the SAMWISE vision-aided inertial navigation estimate algorithms to increase performance during extended duration routes by correcting for navigation estimate drift, as well as automatically initializing the position/orientation estimate to increase ease of use. We are also planning to work more closely with the JSC Wearables Laboratory to develop a roadmap for integration and technology demonstration activities.