Jeremy Straub

The open prototype for educational NanoSats: Fixing the other side of the small satellite cost equation

Government supported nano-satellite launch programs and emerging commercial small satellite launch services are reducing the cost of access to space for educational and other CubeSat projects. The cost and complexity of designing and building these satellites remains a vexing complication for many would be CubeSat aspirants. The Open Prototype for Educational NanoSats (OPEN), a proposed nano-satellite development platform, is described in this paper. OPEN endeavors to reduce the costs and risks associated with educational, government and commercial nano-satellite development. OPEN provides free and publicly available plans for building, testing and operating a versatile, low-cost satellite, based on the standardized CubeSat form-factor. OPEN consists of public-domain educational reference plans, complete with engineering schematics, CAD files, construction and test instructions as well as ancillary reference materials relevant to satellite building and operation. By making the plan, to produce a small but capable spacecraft freely available, OPEN seeks to lower the barriers to access on the other side (non-launch costs) of the satellite cost equation.

Fast relocalization for visual odometry using binary features

State-of-the-art visual odometry algorithms achieve remarkable efficiency and accuracy. Under realistic conditions, however, tracking failures are inevitable and to continue tracking, a recovery strategy is required. In this paper, we propose a relocalization system that enables realtime, 6D pose recovery for wide baselines. Our approach targets specifically resource-constrained hardware such as mobile phones. By exploiting the properties of low-complexity binary feature descriptors, nearest-neighbor search is performed efficiently using Locality Sensitive Hashing. Our method does not require time-consuming offline training of hash tables and it can be applied to any visual odometry system. We provide a thorough evaluation of effectiveness, robustness and runtime on an indoor test sequence with available ground truth poses. We investigate the system parameterization and compare the relocalization performance for the three binary descriptors BRIEF, unscaled BRIEF and ORB. In contrast to previous work on mobile visual odometry, we are able to quickly recover from tracking failures within maps with thousands of 3D feature points.

A Characterization of the Utility of Using Artificial Intelligence to Test Two Artificial Intelligence Systems

An artificial intelligence system, designed for operations in a real-world environment faces a nearly infinite set of possible performance scenarios. Designers and developers, thus, face the challenge of validating proper performance across both foreseen and unforeseen conditions, particularly when the artificial intelligence is controlling a robot that will be operating in close proximity, or may represent a danger, to humans. While the manual creation of test cases allows limited testing (perhaps ensuring that a set of foreseeable conditions trigger an appropriate response), this may be insufficient to fully characterize and validate safe system performance. An approach to validating the performance of an artificial intelligence system using a simple artificial intelligence test case producer (AITCP) is presented. The AITCP allows the creation and simulation of prospective operating scenarios at a rate far exceeding that possible by human testers. Four scenarios for testing an autonomous navigation control system are presented: single actor in two-dimensional space, multiple actors in two-dimensional space, single actor in three-dimensional space, and multiple actors in three-dimensional space. The utility of using the AITCP is compared to that of human testers in each of these scenarios.

An open-source scheduler for small satellites

The limited power generation capability of a small satellite (e.g., a CubeSat) requires robust scheduling. A scheduling approach for small satellites which considers subsystem inter-dependency (where co-operation is required, desirable or prohibited), operational requirements and ground communication windows is presented. The paper considers what the optimal way of scheduled tasks for autonomous operation (required for scheduling when not in communication with ground controllers and desirable at all times during the mission) is. It compares a genetic algorithm-based approach, an exhaustive search-based approach and a heuristic-based approach. Performance maximization is considered (in light of both decision-making time and reducing activity time).

Integrating Model-Based Transmission Reduction into a multi-tier architecture

A multi-tier architecture consists of numerous craft as part of the system, orbital, aerial, and surface tiers. Each tier is able to collect progressively greater levels of information. Generally, craft from lower-level tiers are deployed to a target of interest based on its identification by a higher-level craft. While the architecture promotes significant amounts of science being performed in parallel, this may overwhelm the computational and transmission capabilities of higher-tier craft and links (particularly the deep space link back to Earth). Because of this, a new paradigm in in-situ data processing is required. Model-based transmission reduction (MBTR) is such a paradigm. Under MBTR, each node (whether a single spacecraft in orbit of the Earth or another planet or a member of a multi-tier network) is given an a priori model of the phenomenon that it is assigned to study. It performs activities to validate this model. If the model is found to be erroneous, corrective changes are identified, assessed to ensure their significance for being passed on, and prioritized for transmission. A limited amount of verification data is sent with each MBTR assertion message to allow those that might rely on the data to validate the correct operation of the spacecraft and MBTR engine onboard. Integrating MBTR with a multi-tier framework creates an MBTR hierarchy. Higher levels of the MBTR hierarchy task lower levels with data collection and assessment tasks that are required to validate or correct elements of its model. A model of the expected conditions is sent to the lower level craft; which then engages its own MBTR engine to validate or correct the model. This may include tasking a yet lower level of craft to perform activities. When the MBTR engine at a given level receives all of its component data (whether directly collected or from delegation), it randomly chooses some to validate (by reprocessing the validation data), performs analysis and sends its own results (validation and/or changes of model elements and supporting validation data) to its upstream node. This constrains data transmission to only significant (either because it includes a change or is validation data critical for assessing overall performance) information and reduces the processing requirements (by not having to process insignificant data) at higher-level nodes. This paper presents a framework for multi-tier MBTR and two demonstration mission concepts: an Earth sensornet and a mission to Mars. These multi-tier MBTR concepts are compared to a traditional mission approach.

Multi-Tier Exploration: An Architecture for Dramatically Increasing Mission ROI

It is highly desirable to increase the science-return, as a function of cost, of planetary science missions. While innovative hardware miniaturization techniques are poised to reduce mass and volume requirements (and thus launch costs), this is not a complete solution. A new control paradigm is presented, which seeks to maximize mission science- return via eliminating wasted control delays and allowing concurrent performance of mission objectives by multiple craft. Unlike approaches which have relied on extensive teleoperation or controller-supplied low-level tasking, the proposed approach is based on planetary craft having significant autonomy. This local decision-making seeks to maximize performance of the high-level objectives supplied by controllers. 2,3 , is poised to provide a dramatic increase in science benefit as a function of cost. The Multi-Tier Autonomous Mission Architecture (MAMA) approach provides this substantial benefit by increasing craft utilization through autonomy, deferring most investigation decisions to be made on-planet, and committing resources to a possible target site iteratively. The Multi-Tier Autonomous Mission Architecture proposes a level of autonomy never before demonstrated in a space mission. Under this approach, high-level mission objectives and a general target are provided to onboard mission management software. This software determines, based on initial sensing, what areas have the highest relevance to attaining the specified goals (e.g., finding evidence of a given phenomena). Aerial and, subsequently, ground craft are launched into this region to perform more detailed investigation. Each progressive tier of commitment is made only if analysis of progressively more detailed data continues to support the area being the preferred candidate for mission goal attainment. This highly autonomous approach virtually eliminates time wasted waiting for controller instructions and maximizes the value of the communications link by transmitting predominately data (as opposed to pictures for operator situational awareness, and similar) back to Earth. A description of the Multi-Tier Autonomous Mission Architecture and its technical implementation are presented herein. Three mission plans based on the MAMA architecture, a Mars mission, a near Earth object mission and an Earth-science test/demonstration mission, are also presented. The performance of the Multi-Tier Autonomous Mission Architecture, as compared to traditional mission approaches, can be considered in the context of these prospective missions.

Assessing the Value of the OpenOrbiter Program's Research Experience for Undergraduates

This article presents an assessment of the benefits gained by undergraduate students who participated in the OpenOrbiter Small Spacecraft Development Initiative. It provides an overview of the program and its learning objectives, as they apply to undergraduate students. It compares the learning impact between students who participated and those who assumed leadership roles. Qualitative assessment with regard to benefits is also discussed. The article extrapolates from these results to identify program elements that were particularly instrumental in delivering the positive benefits discussed. Finally, future work is discussed.

A data collection decision-making framework for a multi-tier collaboration of heterogeneous orbital, aerial, and ground craft

An algorithm for the autonomous identification of and tasking to collect additional data required to complete a goal is presented. This assertion-form goal is decomposed autonomously into an initial set of data collection tasks. Once these are completed, information gaps may exist or new information collection requirements may be identified. A utilitymaximization, cost-minimization metric is applied to ascertain what data collection tasks craft should be assigned. This decision making process is performed at each level of the hierarchy, decomposing large-scale needs into progressively smaller assignments. The utility of this control approach is assessed for persistent surveillance and planetary science applications.

Extending the orbital services model beyond computing, communications and sensing

An orbital services model has previously been proposed which is conceptualized in terms of providing orbital services related to a remote sensing mission, typical of a sensornet (e.g., computing, communications and sensing services). This model, however, can be extended to support additional services provided in the orbital environment, which could become available in the near to mid-term future. Examples of these services include power (such as might be provided by a solar power satellite), physical servicing (such as described by the DARPA Phoenix project and others), orbital maneuvering or raising and actuation of other remote craft capabilities. This paper considers the prospective mission capabilities that could be delivered by third-party providers and presents a collaborative mission approach based on the use of these orbital services, instead of or in addition to onboard craft capabilities. It also considers a virtual orbital mission, where an organization conducts a space mission without physically building, launching or owning a space asset, through the use of service procurement from vendors. A pathway to the implementation of this orbital services model is discussed highlighting technical, legal and commercial hurdles that must be overcome to enable this mission approach. A qualitative evaluation of the benefits that could prospectively be provided is undertaken. Also included is a value model which could be used to quantitatively evaluate the approachs suitability (benefits versus costs) for a particular mission concept.

Sensor and computing resource management for a small satellite

A small satellite in a low-Earth orbit (e.g., approximately a 300 to 400 km altitude) has an orbital velocity in the range of 8.5 km/s and completes an orbit approximately every 90 minutes. For a satellite with minimal attitude control, this presents a significant challenge in obtaining multiple images of a target region. Presuming an inclination in the range of 50 to 65 degrees, a limited number of opportunities to image a given target or communicate with a given ground station are available, over the course of a 24-hour period. For imaging needs (where solar illumination is required), the number of opportunities is further reduced. Given these short windows of opportunity for imaging, data transfer, and sending commands, scheduling must be optimized. In addition to the high-level scheduling performed for spacecraft operations, payload-level scheduling is also required. The mission requires that images be post-processed to maximize spatial resolution and minimize data transfer (through removing overlapping regions). The payload unit includes GPS and inertial measurement unit (IMU) hardware to aid in image alignment for the aforementioned. The payload scheduler must, thus, split its energy and computing-cycle budgets between determining an imaging sequence (required to capture the highly-overlapping data required for super-resolution and adjacent areas required for mosaicking), processing the imagery (to perform the super-resolution and mosaicking) and preparing the data for transmission (compressing it, etc.). This paper presents an approach for satellite control, scheduling and operations that allows the cameras, GPS and IMU to be used in conjunction to acquire higher-resolution imagery of a target region.