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 developed a small, wearable 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 device does 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 (or any confined environment) that can integrate with astronauts or moveable equipment. Throughout the course of this project, we made a preliminary definition of the system architecture, concept of operations (CONOPS), data processing pipeline, integrated a carbon dioxide sensor with our navigation system, and the development and integration of an algorithm to enable self-initialization and periodically correct accumulated drift through loop closures. Additionally, we prototyped a self-contained portable system for technology demonstration and algorithmic testing in a variety of representative environments including the ISS mockups within NASA’s Space Vehicle Mockup Facility, NASA’s Human Exploration Research Analog (HERA) facility, and the Aquarius Reef Base during NASA Extreme Environment Mission Operations (NEEMO) 23.
With the goal of providing ISS astronauts with 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 resulted in the definition of key system and functional requirements that were used to guide the development of the prototype wearable kinematic system. Additionally, we 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 collaborated with the JSC Wearables Lab regarding 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 the Draper-developed vision-inertial navigation system in the ground-based analog environments. Additionally, we used Draper’s optical motion tracking facility to validate the vision+inertial position and orientation estimate against a “ground truth” estimate. The vision+inertial estimate was extremely close to the “ground truth” estimate during the length of the testing.
Prior to the development of the prototype system, 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
. We subsequently re-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 is the baseline algorithm going forward to enable online initialization and periodic accumulated drift correction using “loop closures.”
Under Draper Laboratory internal research and development funding, we extended the use of the wearable kinematic system to include the integration of a carbon dioxide sensor for time and location stamping of environmental monitoring data. This was demonstrated with success during NEEMO 23 where the Wearable Kinematic Systems (WKS) identified trends in increases in CO2 over time, as well as the identification of pockets of CO2 within the habitat where there is known to be reduced airflow. This is a key demonstration of the technology that has direct applicability to operations within the ISS. Lastly, we have been in discussions with the EVA (extravehicular activity) Management Office regarding the extension of the technology for tracking ISS EVA astronauts as well as during operations on the lunar surface.