Engineering topics

McHenry, Michael

Publications and source records attributed to McHenry, Michael.

8 records

NASA NTRS2022

Planning for a Martian Road Trip – The Mars2020 Mobility Systems Design

The Perseverance rover landed in Jezero Crateron Mars on February 18, 2021, marking the beginning of anepic road trip across Mars. The guiding principle of thePerseverance rover design was to replicate Curiosity, exceptfor when the new mission objectives mandated a change.The scientific objectives require that Perseverance drivemore quickly and more efficiently through more complexterrain than its predecessors. The mobility system forPerseverance exemplifies this, in that key portions areidentical, yet others have had major upgrades. Key upgradesinclude more tractive and more robust tires, newengineering cameras, a new computer dedicated for imageprocessing, and a more efficient AutoNav software suite.This paper will follow how the scientific objectives led tothe key and driving mobility requirements and how theserequirements were decomposed at the different subsystems.

Stragier, Michael M.↗

NASA NTRS2022

Testing Mars 2020 Flight Software and Hardware in the Surface System Development Environment

The Mars 2020 (M2020) Perseverance Rover is NASA's most advanced planetary rover mission to date. It includes a novel Sample Caching Subsystem (SCS) which will collect rock cores for possible future return to Earth, as well as an improved mobility system with enhanced autonomous navigation which will enable it to traverse faster and farther than prior rovers. The development of both systems required extensive flight software and flight hardware testing. To support this testing, we developed the Surface System Development Environment (SSDEV) and used it for a wide variety of testing. SSDEV is a bundled subset of M2020 Flight Software which runs on commercially available Linux computers and can be combined with multiple backend options for simulation and hardware control. The SSDEV architecture enabled our teams to perform much more testing of flight software and flight hardware than would have otherwise been possible. As a secondary benefit, the SSDEV-based test campaigns also helped our teams enter the operations phase of the mission with greater readiness of operations products and tools. In this paper, we summarize the motivation for SSDEV, provide an overview of the SSDEV architecture, list several examples of how SSDEV was used, and summarize lessons learned. SSDEV is not a substitute for integrated testing with flight-like avionics, but it enabled substantially more testing than would have otherwise been possible and also provided some unique benefits. We recommend architectures like SSDEV to future projects that need to perform extensive hardware and software testing using a limited set of flight-like avionics.

Wai, Dennis↗

NASA NTRS2020

A ROS-based Simulator for Testing the Enhanced Autonomous Navigation of the Mars 2020 Rover

In order to achieve the ambitious objectives of the Mars 2020 (M2020) mission, in particular the ability to autonomously traverse more challenging terrains more efficiently, new surface mobility software was developed for Enhanced Navigation (ENav). That decision was made early in the project, before most of the new surface flight software (FSW) existed, which created a need for a separate framework where the new navigation algorithms could be quickly prototyped and tested, before more realistic FSW-based testbeds became available. The JPL robotics team chose the Robot Operating System [1] (ROS) as the environment in which to test the new ENav algorithms. This made it possible to write the algorithms in the C language required by the FSW, so they could be directly ported over to the flight module later on, while leveraging all the C++ libraries and tools provided by ROS for simulation and testing. The ENav algorithms were developed as a separate C library, and stubs were used to replace any FSW-specific code, such as Event Reporting (EVRs) and data products (DPs). A ROS simulator was developed to generate a rich set of varied 3D terrains representative of the candidate Mars landing sites and simulate the physics of the rover motion, the point cloud perceived by the rover’s stereo vision system, and the new thinking-while-driving (TWD) navigation logic which directs the rover to drive autonomously to user-specified waypoints. To simulate the rover motion and perception, a ROS node was developed that uses a software library called HyperDrive Sim (HDSim), which is a wrapper for the Rover Sequencing and Visualization Program [2] (RSVP). That library provides roverterrain settling, realistic slip modelling, and camera rendering capability based on the rover’s NavCam machine vision models. To simulate the navigation logic, a ROS node was created that initializes and runs the ENav algorithms in a way that mimics the FSW execution, while also providing the capability to load and replay data products, including re-running the recorded inputs through the ENav algorithms for testing. An engineering Graphical User Interface (GUI) was also developed to visualize various elements, such as the rover pose during the drive, the simulated and perceived terrain, the selected local and global paths to the goal, the evaluated candidate paths and the reasons why they were rejected, the keep-in and keep-out zones (KIOZs), etc. Finally, an advanced Monte Carlo (MC) framework that can run many simulations in parallel on the Cloud and automatically generate reports that capture the key ENav performance metrics was developed to evaluate the system in a statisticallymeaningful way. This paper provides an overview of the ROSbased simulator used for testing the M2020 ENav algorithms.

Toupet, Olivier↗

NASA NTRS2020

Core Losses in Co-Rich Inductors with Tunable Permeability

High frequency, low loss power systems enable electrified aircraft propulsion. Filter inductors that reduce noise in high current systems can account for 50% of the motor drive mass. Efficient inductor cores with tunable permeability reduce system mass by producing less heat, that removes heat sink mass. Requirements for filter inductors vary based on the chosen topology, but all inductor cores must operate below saturation levels. As the saturation flux density is limited (less than ~2 T), high differential current applications require cores with low relative permeabilities. The large induced anisotropies possible in Co-rich metal amorphous nanocomposite materials enables gapless inductors with relative permeabilities down to ~20. These materials have fine grain size ~8nm with a faulted, close packed structure. The impact of different processing methods on core losses are presented along with comparison to other low permeability soft magnetic materials.

Leary, Alex↗

NASA NTRS2006

Reduction of User Interaction by Autonomy

This paper describes experiments that quantify the improvement that autonomous behaviors enable in the amount of user interaction required to navigate a robot in urban environments. Many papers have discussed various ways to measure the absolute level of autonomy of a system; we measured the relative improvement of autonomous behaviors over teleoperation across multiple traverses of the same course. We performed four runs each on an 'easy' course and a 'hard' course, where half the runs were teleoperated and half used more autonomous behaviors. Statistics show 40-70% reductions in the amount of time the user interacts with the control station; however, with the behaviors tested, user attention remained on the control station even when he was not interacting. Reducing the need for attention will require better obstacle detection and avoidance and better absolute position estimation.

attention↗

NASA NTRS2006

Detection of Water Hazards for Autonomous Robotic Vehicles

Four methods of detection of bodies of water are under development as means to enable autonomous robotic ground vehicles to avoid water hazards when traversing off-road terrain. The methods involve processing of digitized outputs of optoelectronic sensors aboard the vehicles. It is planned to implement these methods in hardware and software that would operate in conjunction with the hardware and software for navigation and for avoidance of solid terrain obstacles and hazards. The first method, intended for use during the day, is based on the observation that, under most off-road conditions, reflections of sky from water are easily discriminated from the adjacent terrain by their color and brightness, regardless of the weather and of the state of surface waves on the water. Accordingly, this method involves collection of color imagery by a video camera and processing of the image data by an algorithm that classifies each pixel as soil, water, or vegetation according to its color and brightness values (see figure). Among the issues that arise is the fact that in the presence of reflections of objects on the opposite shore, it is difficult to distinguish water by color and brightness alone. Another issue is that once a body of water has been identified by means of color and brightness, its boundary must be mapped for use in navigation. Techniques for addressing these issues are under investigation. The second method, which is not limited by time of day, is based on the observation that ladar returns from bodies of water are usually too weak to be detected. In this method, ladar scans of the terrain are analyzed for returns and the absence thereof. In appropriate regions, the presence of water can be inferred from the absence of returns. Under some conditions in which reflections from the bottom are detectable, ladar returns could, in principle, be used to determine depth. The third method involves the recognition of bodies of water as dark areas in short-wavelength infrared (SWIR) images. This method is based on the fact, well known among experts in remote sensing, that water bodies of any appreciable depth appear very dark in near-infrared, overhead imagery. Even under a thick layer of marine fog, SWIR illumination is present. Hence, this method may work even in the presence of clouds, though it is unlikely to work at night. Snow and ice also exhibit very strong absorption at wavelengths greater than about 1.4 m. Hence, the wavelength range of about 1.5 to 1.6 m might be useable in this method for recognizing water, snow, and ice. One notable drawback of this method is that useful look-ahead distance could be limited by surface reflections. The fourth method, intended for use at night, involves the contrast between water and terrain in thermal-infrared (medium-wavelength infrared) imagery. This method is based on the fact that at night, water is usually warmer than the adjacent terrain. Look-ahead distance could be limited in this method because, for reasons not yet fully understood, water appears to darken in the thermal infrared with increasing distance.

Matthes, Larry↗

NASA NTRS2005

Vision Based Localization in Urban Environments

As part of DARPA's MARS2020 program, the Jet Propulsion Laboratory developed a vision-based system for localization in urban environments that requires neither GPS nor active sensors. System hardware consists of a pair of small FireWire cameras and a standard Pentium-based computer. The inputs to the software system consist of: 1) a crude grid-based map describing the positions of buildings, 2) an initial estimate of robot location and 3) the video streams produced by each camera. At each step during the traverse the system: captures new image data, finds image features hypothesized to lie on the outside of a building, computes the range to those features, determines an estimate of the robot's motion since the previous step and combines that data with the map to update a probabilistic representation of the robot's location. This probabilistic representation allows the system to simultaneously represent multiple possible locations, For our testing, we have derived the a priori map manually using non-orthorectified overhead imagery, although this process could be automated. The software system consists of two primary components. The first is the vision system which uses binocular stereo ranging together with a set of heuristics to identify features likely to be part of building exteriors and to compute an estimate of the robot's motion since the previous step. The resulting visual features and the associated range measurements are software component, a particle-filter based localization system. This system uses the map and the then fed to the second primary most recent results from the vision system to update the estimate of the robot's location. This report summarizes the design of both the hardware and software and will include the results of applying the system to the global localization of a robot over an approximately half-kilometer traverse across JPL'S Pasadena campus.

unmanned-ground vehicles↗

NASA NTRS2004

Advanced mobility avionics : a reconfigurable mirco-avionics platform for the future needs of small planetary rovers and micospacecraft

Future small and micro-missions, such as Mars Scouts and Deep Space probes, require a new look at highly integrated, re-configurable, low power avionics. This paper will present our plans for developing a scalable, configurable, and highly integrated 32-bit embedded platform capable of implementing computationally intensive signal processing and control algorithms in space flight instruments and systems. This platform is designed to service the need of both small and large spacecraft and planetary rovers that will operate within moderate radiation environments. Some of the key characteristics of this platform are its small size, low power, high performance, and flexibility. This estimated 10 fold reduction in both size and power over state-of-the-art processing platforms will enable this new product to act as the core of a low-cost mobility system for a wide range of missions.

reconfigurable↗