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At least 145 records · Page 8

Graphical interfaces for cooperative planning systems

Based on a cognitive task analysis of 5 airline flight crews in a simulator study, researchers have designed a testbed for studying computer aids for en route flight path planning. This testbed runs on a Mac II controlling three color monitors, and is being used to study the design of aids for both dispatchers and flight crews. Specifically, the research focuses on design concepts for developing cooperative problem-solving systems. We use en route flight planning (selecting alternate routes or destinations due to unanticipated weather, traffic, malfunctions, etc.) as the context for studying the design of such systems. Researchers are currently exploring three questions in this test environment: (1) When interacting with a flight planning aid, how does the role of the pilot influence overall system performance; (2) Can the architecture for a cooperative planning system be built around Sacerdoti's (1983) concept of an abstraction hierarchy, where the pilot can interact with the system at many different levels of detail (but where the computer aid by default handles lower level details that the pilot has chosen not to deat with); and (3) Can graphical displays and direct manipulation of these displays provide perceptual enhancements (Larkin and Simon, 1987) of the pilot's problem-solving activities. Information is given in viewgraph form.

Smith, Philip J.↗

Man-machine cooperation in advanced teleoperation

Teleoperation experiments at JPL have shown that advanced features in a telerobotic system are a necessary condition for good results, but that they are not sufficient to assure consistently good performance by the operators. Two or three operators are normally used during training and experiments to maintain the desired performance. An alternative to this multi-operator control station is a man-machine interface embedding computer programs that can perform some of the operator's functions. In this paper we present our first experiments with these concepts, in which we focused on the areas of real-time task monitoring and interactive path planning. In the first case, when performing a known task, the operator has an automatic aid for setting control parameters and camera views. In the second case, an interactive path planner will rank different path alternatives so that the operator will make the correct control decision. The monitoring function has been implemented with a neural network doing the real-time task segmentation. The interactive path planner was implemented for redundant manipulators to specify arm configurations across the desired path and satisfy geometric, task, and performance constraints.

Fiorini, Paolo↗

POSTMAN: Point of Sail Tacking for Maritime Autonomous Navigation

Waves apply significant forces to small boats, in particular when such vessels are moving at a high speed in severe sea conditions. In addition, small high-speed boats run the risk of diving with the bow into the next wave crest during operations in the wavelengths and wave speeds that are typical for shallow water. In order to mitigate the issues of autonomous navigation in rough water, a hybrid controller called POSTMAN combines the concept of POS (point of sail) tack planning from the sailing domain with a standard PID (proportional-integral-derivative) controller that implements reliable target reaching for the motorized small boat control task. This is an embedded, adaptive software controller that uses look-ahead sensing in a closed loop method to perform path planning for safer navigation in rough waters. State-of-the-art controllers for small boats are based on complex models of the vessel's kinematics and dynamics. They enable the vessel to follow preplanned paths accurately and can theoretically control all of the small boat s six degrees of freedom. However, the problems of bow diving and other undesirable incidents are not addressed, and it is questionable if a six-DOF controller with basically a single actuator is possible at all. POSTMAN builds an adaptive capability into the controller based on sensed wave characteristics. This software will bring a muchneeded capability to unmanned small boats moving at high speeds. Previously, this class of boat was limited to wave heights of less than one meter in the sea states in which it could operate. POSTMAN is a major advance in autonomous safety for small maritime craft.

Huntsberger, Terrance L.↗

On-board autonomous attitude maneuver planning for planetary spacecraft using genetic algorithms

A key enabling technology that leads to greater spacecraft autonomy is the capability to autonomously and optimally slew the spacecraft from and to different attitudes while operating under a number of celestial and dynamic constraints. The task of finding an attitude trajectory that meets all the constraints is a formidable one, in particular for orbiting or fly-by spacecraft where the constraints and initial and final conditions are of time-varying nature. This paper presents an approach for attitude path planning that makes full use of a priori constraint knowledge and is computationally tractable enough to be executed on-board a spacecraft. The approach is based on incorporating the constraints into a cost function and using a Genetic Algorithm to iteratively search for and optimize the solution. This results in a directed random search that explores a large part of the solution space while maintaining the knowledge of good solutions from iteration to iteration. A solution obtained this way may be used 'as is' or as an initial solution to initialize additional deterministic optimization algorithms. A number of example simulations are presented including the case examples of a generic Europa Orbiter spacecraft in cruise as well as in orbit around Europa. The search times are typically on the order of minutes, thus demonstrating the viability of the presented approach. The results are applicable to all future deep space missions where greater spacecraft autonomy is required. In addition, onboard autonomous attitude planning greatly facilitates navigation and science observation planning, benefiting thus all missions to planet Earth as well.

genetic algorithm↗

A vision system for a Mars rover

A Mars rover must be able to sense its local environment with sufficient resolution and accuracy to avoid local obstacles and hazards while moving a significant distance each day. Power efficiency and reliability are extremely important considerations, making stereo correlation an attractive method of range sensing compared to laser scanning, if the computational load and correspondence errors can be handled. Techniques for treatment of these problems, including the use of more than two cameras to reduce correspondence errors and possibly to limit the computational burden of stereo processing, have been tested at JPL. Once a reliable range map is obtained, it must be transformed to a plan view and compared to a stored terrain database, in order to refine the estimated position of the rover and to improve the database. The slope and roughness of each terrain region are computed, which form the basis for a traversability map allowing local path planning. Ongoing research and field testing of such a system is described.

Wilcox, Brian H.↗

Avoiding space robot collisions utilizing the NASA/GSFC tri-mode skin sensor

Sensor based robot motion planning research has primarily focused on mobile robots. Consider, however, the case of a robot manipulator expected to operate autonomously in a dynamic environment where unexpected collisions can occur with many parts of the robot. Only a sensor based system capable of generating collision free paths would be acceptable in such situations. Recently, work in this area has been reported in which a deterministic solution for 2DOF systems has been generated. The arm was sensitized with 'skin' of infra-red sensors. We have proposed a heuristic (potential field based) methodology for redundant robots with large DOF's. The key concepts are solving the path planning problem by cooperating global and local planning modules, the use of complete information from the sensors and partial (but appropriate) information from a world model, representation of objects with hyper-ellipsoids in the world model, and the use of variational planning. We intend to sensitize the robot arm with a 'skin' of capacitive proximity sensors. These sensors were developed at NASA, and are exceptionally suited for the space application. In the first part of the report, we discuss the development and modeling of the capacitive proximity sensor. In the second part we discuss the motion planning algorithm.

Prinz, F. B.↗

SIRIUS: Simulation Infrastructure for Research on Interoperating Unmanned Systems

This paper presents the Simulation Infrastructure for Research on Interoperating Unmanned Systems (SIRIUS), a research framework for simulation and analysis of future conceptual Urban Air Mobility (UAM) operations. SIRIUS is being developed under the auspices of the NASA Air Traffic Management eXploration project, UAM subproject (ATM-X UAM). SIRIUS provides an intuitive, highly configurable graphical user interface to design complex traffic scenarios and airspace configurations representative of conceptual UAM operations. Aircraft simulated with SIRIUS can be equipped with flight-tested capabilities for detect and avoid (DAA), geofencing, distributed merging and spacing, path conformance, and path planning while executing time-constrained, 4D trajectories generated by a UAM ground operations system. Central to the design of the SIRIUS simulation framework is the capability to evaluate the integration and interoperability of ground-based separation services (e.g., strategic separation) with extended DAA functionality (e.g., path monitoring, separation provision, merging and spacing, etc.) The simulation environment also supports modelling of wind, navigation, and sensor uncertainties, as well as communication delays. SIRIUS enables distributed simulation of large-scale scenarios. An interactive graphical analysis capability helps isolate, visualize, and compare relevant vehicle state data and widely used measures of performance metrics across multiple scenarios.

Andrew Peters↗

Enroute flight planning: Evaluating design concepts for the development of cooperative problem-solving systems

There are many problem-solving tasks that are too complex to fully automate given the current state of technology. Nevertheless, significant improvements in overall system performance could result from the introduction of well-designed computer aids. We have been studying the development of cognitive tools for one such problem-solving task, enroute flight path planning for commercial airlines. Our goal has been two-fold. First, we have been developing specific system designs to help with this important practical problem. Second, we have been using this context to explore general design concepts to guide in the development of cooperative problem-solving systems. These design concepts are described below, along with illustrations of their application.

Smith, Philip J.↗

A linguistic geometry for 3D strategic planning

This paper is a new step in the development and application of the Linguistic Geometry. This formal theory is intended to discover the inner properties of human expert heuristics, which have been successful in a certain class of complex control systems, and apply them to different systems. In this paper we investigate heuristics extracted in the form of hierarchical networks of planning paths of autonomous agents. Employing Linguistic Geometry tools the dynamic hierarchy of networks is represented as a hierarchy of formal attribute languages. The main ideas of this methodology are shown in this paper on the new pilot example of the solution of the extremely complex 3D optimization problem of strategic planning for the space combat of autonomous vehicles. This example demonstrates deep and highly selective search in comparison with conventional search algorithms.

Stilman, Boris↗

Silhouette-Informed Trajectory Generation Through a Wire Maze for Small UAS

Current rapidly-exploring random tree (RRT) algorithms rely on proximity query packages that often include collision checkers, tolerance verification, and distance computation algorithms for the generation of safe paths. In this paper, we broaden the information available to the path-planning algorithm by incorporating silhouette information of nearby obstacles in conflict. A silhouette-informed tree (SIT) is generated through the flight-safe region of a wire maze for a single unmanned aerial system (UAS). The silhouette is used to extract local geometric information of nearby obstacles and provide path alternatives around these obstacles. Thus, focusing the search for the generation of new tree branches near these obstacles, and decreasing the number of samples required to explore the narrow corridors within the wire maze. The SIT is then processed to extract a path that connects the initial location of the UAS with the goal, reduce the number of line segments in this path if possible, and smooth the resulting path using Pythagorean Hodograph Bezier curves. To ensure that the smoothed path remains in the flight-safe region of the configuration space, a tolerance verification algorithm for Bezier curves and convex polytopes in three dimensions is proposed. Lastly, temporal specifications are imposed on the smoothed path in the shape of an arbitrary speed profile.

Puig-Navarro, Javier↗

Comparison of Acoustic Models and Trajectory Generation Methods for an Acoustically-Aware Aircraft

This paper presents a comparison of trajectory generation methodologies using acoustic source noise models of different fidelity for motion planning for an acoustically-aware aircraft subject to constraints on the vehicle dynamic performance, mission, and acoustic footprint of the vehicle at a set of (three-dimensional) observer locations. The performance of a pre-mission Bézier curve-based planner and a (near) real-time stochastic model predictive control planner are compared. Additionally, a comparison is made between the motion planning performance using a lower-fidelity acoustic model based on propeller tip Mach number and omni-directional sound power radiation, and a hemisphere-based higher-fidelity acoustic model. It is demonstrated that the asymmetry in hemisphere-based acoustic model can be exploited for improved flight path planning and trajectory-tracking performance in the presence of acoustic constraints.

Kasey A Ackerman↗

Operating Small Sat Swarms as a Single Entity: Introducing SODA

NASA's decadal survey determined that simultaneous measurements from a 3D volume of space are advantageous for a variety of studies in space physics and Earth science. Therefore, swarm concepts with multiple spacecraft in close proximity are a growing topic of interest in the small satellite community. Among the capabilities needed for swarm missions is a means to maintain operator-specified geometry, alignment, or separation. Swarm stationkeeping poses a planning challenge due to the limited scalability of ground resources. To address scalable control of orbital dynamics, we introduce SODA - Swarm Orbital Dynamics Advisor - a tool that accepts high-level configuration commands and provides the orbital maneuvers needed to achieve the desired type of swarm relative motion. Rather than conventional path planning, SODA's innovation is the use of artificial potential functions to define boundaries and keepout regions. The software architecture includes high fidelity propagation, accommodates manual or automated inputs, displays motion animations, and returns maneuver commands and analytical results. Currently, two swarm types are enabled: in-train distribution and an ellipsoid volume container. Additional swarm types, simulation applications, and orbital destinations are in planning stages.

Conn, Tracie↗

Operating Small Sat Swarms as a Single Entity: Introducing SODA

NASA's decadal survey determined that simultaneous measurements from a 3D volume of space are advantageous for a variety of studies in space physics and Earth science. Therefore, swarm concepts with multiple spacecraft in close proximity are a growing topic of interest in the small satellite community. Among the capabilities needed for swarm missions is a means to maintain operator-specified geometry, alignment, or separation. Swarm stationkeeping poses a planning challenge due to the limited scalability of ground resources. To address scalable control of orbital dynamics, we introduce SODA - Swarm Orbital Dynamics Advisor - a tool that accepts high-level configuration commands and provides the orbital maneuvers needed to achieve the desired type of swarm relative motion. Rather than conventional path planning, SODA's innovation is the use of artificial potential functions to define boundaries and keepout regions. The software architecture includes high fidelity propagation, accommodates manual or automated inputs, displays motion animations, and returns maneuver commands and analytical results. Currently, two swarm types are enabled: in-train distribution and an ellipsoid volume container. Additional swarm types, simulation applications, and orbital destinations are in planning stages.

Conn, Tracie↗

Lunar Science Investigations and Exploration in Celestial Mapping System

Introduction: As NASA expands the mission portfolio on the lunar surface, there is a need for applications with a broad range of analytical and functional capabilities that can be simultaneously deployed onto multiple mobile and desktop platforms to perform in-situ operations and hence enabling extensive Lunar exploration. Celestial Mapping System (CMS) [1,2] is developed to address the need for tools for science investigations, mission planning, operations and support for planetary sciences. Built on top of NASA WorldWind libraries, CMS can be simultaneously deployed onto multiple platforms, has the flexibility to update to the latest imagery and terrain datasets as they are being acquired (in real time) before and/or during the exploration mission and has the potential to enable traverse path planning suited for rovers, EVA and surface mobility units. It can provide critical functionalities such as equipment planning and optimized placement on Lunar surface, line of sight analysis to inform the coverage area for various equipment, powerful measurement tools based on 3D terrain, 3D COLLADA models to represent rovers, humans and equipment, visualization of derived mapping products (e.g. resource maps), and a data engine for hosting new observations that are not available in other contemporary lunar data tools [1]. Visualization of PSRs: The current presentation focuses on the work performed by the authors, to consume a unique dataset of super-enhanced images of the permanently shadowed regions (PSRs) at the lunar poles which were produced by the Hyper-effective nOise Removal U-net Software (HORUS) tool [3]. This tool was developed in direct support of NASA's VIPER and Artemis programs to enhance the extremely low-light images of the interior of PSRs and provide the first-time ability to see within these regions at and discern surface features (i.e. boulders and craters) down to 3 meters in size. We focused on the region near Nobili crater near Lunar south pole, selected site for VIPER mission and stitched several images to create a high-resolution map within one of the PSR of Nobile crater. Line of Sight Analysis and Traverse Planning in PSRs: We have developed an in-built line of sight analysis (LOS) tool in CMS that analyzes the terrain profile and obstructions and provides the visibility of a given terrain for a remote observer. This tool was utilized to perform viewshed analysis to investigate the area inside the PSR, a remote observer such as a rover could see without actually crossing the region. Figure 1 shows the viewshed analysis on the PSR in Nobile region. The yellow pin shows the observer location outside the PSR. The yellow area shows the visible part of PSR. The obstructed area with no visibility for the observer is shown in red. Figure 1: (left) PSR image on top of a high-resolution mosaic of sunlit images of a crater, in Nobile region (right) Viewshed Analysis of the same PSR with observer location shown by yellow pin. This analysis was extended further to set different heights for various observers and then perform the viewshed analysis. Combining the different visibility profiles can help designing improved traverses within the crater. Future plans: Eventually, HORUS datasets will be integrated into CMS as a layer in selected lunar polar regions. Hazard Maps will then be created based on terrain analysis in those regions. This integration will enable multiple scientific and exploration applications, such as designing traverses within PSRs, analyzing potential landing and science mission targets, investigating the meter-scale geomorphology of PSRs, including craters, boulder, surface roughness, mass wasting features and other indications of the presence of water-ice and other volatiles. Acknowledgments: CMS developers team including Kaitlyn J. Dickinson, Tyler A. Lucarz, Tyler W. Choi from USRA, NASA WorldWind Advisory team including Mark Peterson and Guillermo Miguel Del Castillo, HORUS team member V.T. Bickel, Robinson, M., LRO MOON LROC 2 EDR V1.0, LRO-L-LROC-2-EDR-V1.0, NASA Planetary Data System (PDS), 2009. https://doi.org/10.17189/1520643 References: [1] https://celestial.arc.nasa.gov [2] Agrawal et. al. “Celestial Mapping System for Lunar Surface Mapping and Analytics”, Lunar Surface Innovation Consortium, 2021 [3] Bickel V. et al. (2021) Nat Commun 12, 5607

Lunar Mapping↗

Using Planning, Scheduling and Execution for Autonomous Mars Rover Operations

With each new rover mission to Mars, rovers are traveling significantly longer distances. This distance increase raises not only the opportunities for science data collection, but also amplifies the amount of environment and rover state uncertainty that must be handled in rover operations. This paper describes how planning, scheduling and execution techniques can be used onboard a rover to autonomously generate and execute rover activities and in particular to handle new science opportunities that have been identified dynamically. We also discuss some of the particular challenges we face in supporting autonomous rover decision-making. These include interaction with rover navigation and path-planning software and handling large amounts of uncertainty in state and resource estimations. Finally, we describe our experiences in testing this work using several Mars rover prototypes in a realistic environment.

automated rover operations↗

Spacecraft Attitude Maneuver Planning Using Genetic Algorithms

A key enabling technology that leads to greater spacecraft autonomy is the capability to autonomously and optimally slew the spacecraft from and to different attitudes while operating under a number of celestial and dynamic constraints. The task of finding an attitude trajectory that meets all the constraints is a formidable one, in particular for orbiting or fly-by spacecraft where the constraints and initial and final conditions are of time-varying nature. This approach for attitude path planning makes full use of a priori constraint knowledge and is computationally tractable enough to be executed onboard a spacecraft. The approach is based on incorporating the constraints into a cost function and using a Genetic Algorithm to iteratively search for and optimize the solution. This results in a directed random search that explores a large part of the solution space while maintaining the knowledge of good solutions from iteration to iteration. A solution obtained this way may be used as is or as an initial solution to initialize additional deterministic optimization algorithms. A number of representative case examples for time-fixed and time-varying conditions yielded search times that are typically on the order of minutes, thus demonstrating the viability of this method. This approach is applicable to all deep space and planet Earth missions requiring greater spacecraft autonomy, and greatly facilitates navigation and science observation planning.

Kornfeld, Richard P.↗

Architecture for Control of the K9 Rover

Software featuring a multilevel architecture is used to control the hardware on the K9 Rover, which is a mobile robot used in research on robots for scientific exploration and autonomous operation in general. The software consists of five types of modules: Device Drivers - These modules, at the lowest level of the architecture, directly control motors, cameras, data buses, and other hardware devices. Resource Managers - Each of these modules controls several device drivers. Resource managers can be commanded by either a remote operator or the pilot or conditional-executive modules described below. Behaviors and Data Processors - These modules perform computations for such functions as planning paths, avoiding obstacles, visual tracking, and stereoscopy. These modules can be commanded only by the pilot. Pilot - The pilot receives a possibly complex command from the remote operator or the conditional executive, then decomposes the command into (1) more-specific commands to the resource managers and (2) requests for information from the behaviors and data processors. Conditional Executive - This highest-level module interprets a command plan sent by the remote operator, determines whether resources required for execution of the plan are available, monitors execution, and, if necessary, selects an alternate branch of the plan.

Bresina, John L.↗