Min Li, Miao Wang, Guoqing Wang, Yong Chen, Kelin Zhong
Predictive mental workload model is an important tool for evaluating early single-pilot operations (SPO) system design and can be used to explore the impact of different function allocation decisions before prototype or simulator implementation. To build this model, this paper proposes a methodology based on task analysis. Firstly, it selects the approach and landing scenario of the current two-pilot operations (TCO) and completes the task description of the TCO using the hierarchical task analysis. Secondly, it identifies the function allocation requirements for the transition from TCO to SPO using the work domain analysis and proposes the original function allocation decisions based on the SPO’s system framework. Finally, it creates the predictive mental workload model for evaluating different SPO system design options based on temporal network and multiple resource theory. The researchers use the created model to evaluate the original function allocation decisions and find that the designed SPO system has instantaneous workload values that exceed the upper limit at multiple time points. By analyzing the causes of these problems, the researchers introduce audible warnings and visual indicators to the SPO system to improve design decisions and evaluate these decisions. The results show that the continuous workload profile and overall average workload of the redesigned SPO system are better than the current TCO system, and also prove that the predictive mental workload model can be well applied to evaluate the system design of early SPO.
{"title":"Predictive Mental Workload Modeling Methodology for Single-Pilot Operations System Design","authors":"Min Li, Miao Wang, Guoqing Wang, Yong Chen, Kelin Zhong","doi":"10.2514/1.i011314","DOIUrl":"https://doi.org/10.2514/1.i011314","url":null,"abstract":"Predictive mental workload model is an important tool for evaluating early single-pilot operations (SPO) system design and can be used to explore the impact of different function allocation decisions before prototype or simulator implementation. To build this model, this paper proposes a methodology based on task analysis. Firstly, it selects the approach and landing scenario of the current two-pilot operations (TCO) and completes the task description of the TCO using the hierarchical task analysis. Secondly, it identifies the function allocation requirements for the transition from TCO to SPO using the work domain analysis and proposes the original function allocation decisions based on the SPO’s system framework. Finally, it creates the predictive mental workload model for evaluating different SPO system design options based on temporal network and multiple resource theory. The researchers use the created model to evaluate the original function allocation decisions and find that the designed SPO system has instantaneous workload values that exceed the upper limit at multiple time points. By analyzing the causes of these problems, the researchers introduce audible warnings and visual indicators to the SPO system to improve design decisions and evaluate these decisions. The results show that the continuous workload profile and overall average workload of the redesigned SPO system are better than the current TCO system, and also prove that the predictive mental workload model can be well applied to evaluate the system design of early SPO.","PeriodicalId":50260,"journal":{"name":"Journal of Aerospace Information Systems","volume":"55 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135888103","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Chuhao Deng, Hong-Cheol Choi, Hyunsang Park, Inseok Hwang
The continuous growth of demand on commercial airlines has made it crucial to guarantee the safety of airspace operations. Although adverse events are rare, once they happen, they can cause unpredictable risky factors and degrade airspace efficiency. Thus, studying historical air traffic data to discover precursors, features, or events that contribute to the occurrence of the adverse event in the future is important and has gained interest in recent years. In this paper, a novel and real-time applicable temporal precursor discovery (TPD) framework based on the long short-term memory neural network and the feature attention mechanism is proposed. The feature attention mechanism enables the framework to pay attention to certain features at a certain time, and the attention score is defined as the temporal precursor. The temporal precursor reflects the rationale behind the neural network’s prediction at each time step, providing a data-driven explanation of how the adverse event occurs. The proposed TPD framework was tested with real air traffic data and weather data recorded at Incheon International Airport in South Korea in 2019.
{"title":"Temporal Precursor Discovery Using Long Short-Term Memory with Feature Attention","authors":"Chuhao Deng, Hong-Cheol Choi, Hyunsang Park, Inseok Hwang","doi":"10.2514/1.i011225","DOIUrl":"https://doi.org/10.2514/1.i011225","url":null,"abstract":"The continuous growth of demand on commercial airlines has made it crucial to guarantee the safety of airspace operations. Although adverse events are rare, once they happen, they can cause unpredictable risky factors and degrade airspace efficiency. Thus, studying historical air traffic data to discover precursors, features, or events that contribute to the occurrence of the adverse event in the future is important and has gained interest in recent years. In this paper, a novel and real-time applicable temporal precursor discovery (TPD) framework based on the long short-term memory neural network and the feature attention mechanism is proposed. The feature attention mechanism enables the framework to pay attention to certain features at a certain time, and the attention score is defined as the temporal precursor. The temporal precursor reflects the rationale behind the neural network’s prediction at each time step, providing a data-driven explanation of how the adverse event occurs. The proposed TPD framework was tested with real air traffic data and weather data recorded at Incheon International Airport in South Korea in 2019.","PeriodicalId":50260,"journal":{"name":"Journal of Aerospace Information Systems","volume":"71 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135884951","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Jason Swope, Faiz Mirza, Emily Dunkel, Alberto Candela, Steve Chien, Alexandra Holloway, Damon Russell, Joe Sauvageau, Douglas Sheldon, Mark Fernandez
Future space missions will process and analyze imagery on board as well as plan and act more autonomously, placing greater demands on flight computing. Traditional flight hardware provides modest computing power, even when compared to common laptop and desktop computers. A new generation of commercial-off-the-shelf (COTS) processors designed for commercial electronics such as cell phones and tablets, such as the Qualcomm Snapdragon, deliver significant compute in a small size, weight, and power; and they offer hardware acceleration in the form of graphics processing units and digital signal processors. We benchmark a variety of instrument processing and mission planning software on a Qualcomm Snapdragon system on a chip currently hosted by Hewlett Packard Enterprise’s Spaceborne Computer-2 on board the International Space Station to highlight the potential of using embedded COTS processors on future space missions.
{"title":"Benchmarking Space Mission Applications on the Snapdragon Processor Onbaord the ISS","authors":"Jason Swope, Faiz Mirza, Emily Dunkel, Alberto Candela, Steve Chien, Alexandra Holloway, Damon Russell, Joe Sauvageau, Douglas Sheldon, Mark Fernandez","doi":"10.2514/1.i011217","DOIUrl":"https://doi.org/10.2514/1.i011217","url":null,"abstract":"Future space missions will process and analyze imagery on board as well as plan and act more autonomously, placing greater demands on flight computing. Traditional flight hardware provides modest computing power, even when compared to common laptop and desktop computers. A new generation of commercial-off-the-shelf (COTS) processors designed for commercial electronics such as cell phones and tablets, such as the Qualcomm Snapdragon, deliver significant compute in a small size, weight, and power; and they offer hardware acceleration in the form of graphics processing units and digital signal processors. We benchmark a variety of instrument processing and mission planning software on a Qualcomm Snapdragon system on a chip currently hosted by Hewlett Packard Enterprise’s Spaceborne Computer-2 on board the International Space Station to highlight the potential of using embedded COTS processors on future space missions.","PeriodicalId":50260,"journal":{"name":"Journal of Aerospace Information Systems","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135888522","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Seth Roffe, Himanshu Akolkar, Alan George, Ryad Benosman
Neuromorphic event-based networks use asynchronous time-dependent information to extract features from input data that can allow for edge-based distributed applications such as object recognition. The noise resilience properties of such networks, especially in the context of space applications, are yet to be explored. In this paper, we use the hierarchy of time surfaces (HOTS) algorithm, which is one of the neuromorphic algorithms, to understand the least and most resilient modules in a neuromorphic network. The HOTS algorithm relies on the computing of time surfaces that maps the temporal delays between neighboring pixels into normalized features that involve many computations that are also found in other neuromorphic networks such as exponential decays, distance computations, etcetera. We implemented HOTS on a Digilent PYNQ board with a Xilinx Zynq 7020 system on a chip, and we subjected the boards running the HOTS network inference to neutron radiation at the Los Alamos Neutron Science Center. Furthermore, we used simulation models from our previous similar experiments on the event-based sensor to create a neutron induced noise model to quantify the effect of this noise on the overall performance of the network. This experiment provides the preliminary measurements of the reliability of the HOTS algorithm and proposes methods to create a more reliable HOTS architecture in future spacecraft missions.
{"title":"Radiation-Induced Noise Resilience of Neuromorphic Architectures","authors":"Seth Roffe, Himanshu Akolkar, Alan George, Ryad Benosman","doi":"10.2514/1.i011192","DOIUrl":"https://doi.org/10.2514/1.i011192","url":null,"abstract":"Neuromorphic event-based networks use asynchronous time-dependent information to extract features from input data that can allow for edge-based distributed applications such as object recognition. The noise resilience properties of such networks, especially in the context of space applications, are yet to be explored. In this paper, we use the hierarchy of time surfaces (HOTS) algorithm, which is one of the neuromorphic algorithms, to understand the least and most resilient modules in a neuromorphic network. The HOTS algorithm relies on the computing of time surfaces that maps the temporal delays between neighboring pixels into normalized features that involve many computations that are also found in other neuromorphic networks such as exponential decays, distance computations, etcetera. We implemented HOTS on a Digilent PYNQ board with a Xilinx Zynq 7020 system on a chip, and we subjected the boards running the HOTS network inference to neutron radiation at the Los Alamos Neutron Science Center. Furthermore, we used simulation models from our previous similar experiments on the event-based sensor to create a neutron induced noise model to quantify the effect of this noise on the overall performance of the network. This experiment provides the preliminary measurements of the reliability of the HOTS algorithm and proposes methods to create a more reliable HOTS architecture in future spacecraft missions.","PeriodicalId":50260,"journal":{"name":"Journal of Aerospace Information Systems","volume":"171 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136097992","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Kwangjin Yang, Songhyon Kim, Younggun Lee, Changyoung Jang, Yong-Duk Kim
A novel new air combat algorithm is proposed, which is based on the knowledge extracted from the experience of human pilots. First, to implement a fighter that maneuvers based on manual control, the maneuver form of the fighter is analyzed and represented as a block. Second, the blocks for each function are connected based on their relationship, and a flow diagram is presented according to the engagement situation of the adversary and ownship. Third, a behavior tree model is applied as a decision-making model to implement the flow diagram as a simulation program. The behavior tree offers good scalability because nonleaf nodes can be added when sophisticated and complex decision-making is required. The proposed method has the advantage of making all maneuvers performed by the algorithm understandable and interpretable. Additionally, it can replace expensive and dangerous dogfighting training for student pilots because the proposed model can emulate maneuvers that manned pilots would perform. To verify the proposed method, the evaluation criteria from the AlphaDogfight Trials are equally applied in the simulation. The experimental results demonstrate that the proposed method has superior engagement capability as compared to the existing air-to-air combat models.
{"title":"Manual-Based Automated Maneuvering Decisions for Air-to-Air Combat","authors":"Kwangjin Yang, Songhyon Kim, Younggun Lee, Changyoung Jang, Yong-Duk Kim","doi":"10.2514/1.i011234","DOIUrl":"https://doi.org/10.2514/1.i011234","url":null,"abstract":"A novel new air combat algorithm is proposed, which is based on the knowledge extracted from the experience of human pilots. First, to implement a fighter that maneuvers based on manual control, the maneuver form of the fighter is analyzed and represented as a block. Second, the blocks for each function are connected based on their relationship, and a flow diagram is presented according to the engagement situation of the adversary and ownship. Third, a behavior tree model is applied as a decision-making model to implement the flow diagram as a simulation program. The behavior tree offers good scalability because nonleaf nodes can be added when sophisticated and complex decision-making is required. The proposed method has the advantage of making all maneuvers performed by the algorithm understandable and interpretable. Additionally, it can replace expensive and dangerous dogfighting training for student pilots because the proposed model can emulate maneuvers that manned pilots would perform. To verify the proposed method, the evaluation criteria from the AlphaDogfight Trials are equally applied in the simulation. The experimental results demonstrate that the proposed method has superior engagement capability as compared to the existing air-to-air combat models.","PeriodicalId":50260,"journal":{"name":"Journal of Aerospace Information Systems","volume":"87 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135696387","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Rojo Princy Andrianantara, Georges Ghazi, Ruxandra Mihaela Botez
This paper presents a methodology developed at the Laboratory of Applied Research in Active Controls, Avionics, and Aeroservoelasticity to identify a performance model of the CF34-8C5B1 turbofan engine powering the CRJ-700 regional jet aircraft from simulated flight data using artificial neural networks (ANNs). For this purpose, a qualified virtual research simulator was used to conduct different types of flight tests and to collect engine data under a wide range of operating conditions. The collected data were then used to create a comprehensive database for the training of the ANN model. This process was performed using the Bayesian regularization algorithm available in the MATLAB Neural Networks Toolbox, followed by a study to identify the optimal network architecture, namely, the number of layers and the number of neurons. The validation of the methodology was accomplished by comparing the model predictions with a set of flight data collected with the flight simulator for different flight conditions and flight regimes including takeoff, climb, cruise, and descent. The results showed that the model was able to predict the engine performance in terms of fan speed, core speed, inlet turbine temperature, net thrust, and fuel flow with less than 5% relative error.
{"title":"Performance Model Identification of the General Electric CF34-8C5B1 Turbofan Using Neural Networks","authors":"Rojo Princy Andrianantara, Georges Ghazi, Ruxandra Mihaela Botez","doi":"10.2514/1.i011220","DOIUrl":"https://doi.org/10.2514/1.i011220","url":null,"abstract":"This paper presents a methodology developed at the Laboratory of Applied Research in Active Controls, Avionics, and Aeroservoelasticity to identify a performance model of the CF34-8C5B1 turbofan engine powering the CRJ-700 regional jet aircraft from simulated flight data using artificial neural networks (ANNs). For this purpose, a qualified virtual research simulator was used to conduct different types of flight tests and to collect engine data under a wide range of operating conditions. The collected data were then used to create a comprehensive database for the training of the ANN model. This process was performed using the Bayesian regularization algorithm available in the MATLAB Neural Networks Toolbox, followed by a study to identify the optimal network architecture, namely, the number of layers and the number of neurons. The validation of the methodology was accomplished by comparing the model predictions with a set of flight data collected with the flight simulator for different flight conditions and flight regimes including takeoff, climb, cruise, and descent. The results showed that the model was able to predict the engine performance in terms of fan speed, core speed, inlet turbine temperature, net thrust, and fuel flow with less than 5% relative error.","PeriodicalId":50260,"journal":{"name":"Journal of Aerospace Information Systems","volume":"35 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134958343","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Matthew B. Rhudy, Mario L. Fravolini, Marcello R. Napolitano
Navigation is a critical task for the operations of both manned and unmanned aircraft systems. Current positioning systems rely primarily on satellite systems such as the Global Positioning System (GPS) or alternative sensor fusion algorithms, which typically require vision sensing and processing. Due to the possibility of temporary GPS outages and/or GPS jamming, it is critical for aircraft sensing systems to predict the position as well as the ground velocity of the aircraft in the absence of GPS signals. This work proposes two state estimation algorithms for predicting the position and ground velocity of aircraft. These methods do not require vision sensors or aircraft dynamic model information, thus providing a portable approach applicable to any aircraft. The proposed methods consider infrequent GPS position updates. Although not completely GPS free, these algorithms do not require GPS velocity measurements and can predict the aircraft position in between the position updates. The proposed methods use the information filter and unscented information filter; they are first validated using unmanned aircraft flight data and later applied to flight data from a high-speed manned military trainer jet. The results indicate the effectiveness of this approach for model-free position and ground velocity estimation.
{"title":"Model-Free Ground Velocity and Position Estimation for Manned and Unmanned Aircraft","authors":"Matthew B. Rhudy, Mario L. Fravolini, Marcello R. Napolitano","doi":"10.2514/1.i011221","DOIUrl":"https://doi.org/10.2514/1.i011221","url":null,"abstract":"Navigation is a critical task for the operations of both manned and unmanned aircraft systems. Current positioning systems rely primarily on satellite systems such as the Global Positioning System (GPS) or alternative sensor fusion algorithms, which typically require vision sensing and processing. Due to the possibility of temporary GPS outages and/or GPS jamming, it is critical for aircraft sensing systems to predict the position as well as the ground velocity of the aircraft in the absence of GPS signals. This work proposes two state estimation algorithms for predicting the position and ground velocity of aircraft. These methods do not require vision sensors or aircraft dynamic model information, thus providing a portable approach applicable to any aircraft. The proposed methods consider infrequent GPS position updates. Although not completely GPS free, these algorithms do not require GPS velocity measurements and can predict the aircraft position in between the position updates. The proposed methods use the information filter and unscented information filter; they are first validated using unmanned aircraft flight data and later applied to flight data from a high-speed manned military trainer jet. The results indicate the effectiveness of this approach for model-free position and ground velocity estimation.","PeriodicalId":50260,"journal":{"name":"Journal of Aerospace Information Systems","volume":"606 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136309196","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Aerial wildfire operations are high risk and account for a large number of firefighter deaths. The increasing intensity of wildfires is driving a surge in aerial operations, as well as interest to improve system safety and performance. In this work, wildfire aviation mishaps documented using the Aviation Safety Communiqué (SAFECOM) system are analyzed using a previously developed framework for hazard extraction and analysis of trends. Hazards and specific failure modes are extracted from the narrative data in SAFECOM forms using natural language processing techniques. Metrics for each hazard (including the frequency, rate, and severity) are calculated. We examine whether these metrics change over time and whether they are related to metadata, such as region and aircraft type. The results of the hazard analysis are presented in a risk matrix, identifying the highest and lowest risk hazards based on the rate of occurrence and average severity. The analysis of all SAFECOM reports indicated that the jumper operations hazards were classified as high risk; whereas the hydraulic fluid malfunctions, bucket or tank failures, retardant loading and jettison failures, prescribed burn operations, cargo letdown failures, and severe weather were classified as serious risk. However, when applied to a specific operational scenario, risk levels change across hazards.
{"title":"Natural-Language-Processing-Enabled Quantitative Risk Analysis of Aerial Wildfire Operations","authors":"Sequoia Andrade, Hannah S. Walsh","doi":"10.2514/1.i011243","DOIUrl":"https://doi.org/10.2514/1.i011243","url":null,"abstract":"Aerial wildfire operations are high risk and account for a large number of firefighter deaths. The increasing intensity of wildfires is driving a surge in aerial operations, as well as interest to improve system safety and performance. In this work, wildfire aviation mishaps documented using the Aviation Safety Communiqué (SAFECOM) system are analyzed using a previously developed framework for hazard extraction and analysis of trends. Hazards and specific failure modes are extracted from the narrative data in SAFECOM forms using natural language processing techniques. Metrics for each hazard (including the frequency, rate, and severity) are calculated. We examine whether these metrics change over time and whether they are related to metadata, such as region and aircraft type. The results of the hazard analysis are presented in a risk matrix, identifying the highest and lowest risk hazards based on the rate of occurrence and average severity. The analysis of all SAFECOM reports indicated that the jumper operations hazards were classified as high risk; whereas the hydraulic fluid malfunctions, bucket or tank failures, retardant loading and jettison failures, prescribed burn operations, cargo letdown failures, and severe weather were classified as serious risk. However, when applied to a specific operational scenario, risk levels change across hazards.","PeriodicalId":50260,"journal":{"name":"Journal of Aerospace Information Systems","volume":"86 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136312829","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
In order to evaluate the feasibility of planetary exploration missions, it is imperative to construct planetary terrain environments on the ground. Nevertheless, the implementation of this method is characterized by time-consuming and challenging factors. By contrast, resorting to simulation approaches represents a cost-effective and high-efficiency alternative, which can facilitate the simulation validation of planetary rover exploration missions in an effective manner. In this paper, a modular planet rover simulation platform is proposed; by building and overlaying multiple feature layers corresponding to the surface of the planet, we realize the simulation of high-resolution fine terrain and through adjusting the terrain parameters to meet the needs of different simulated terrain. The experimental results show that we have built a scene to satisfy the requirements of visual effects and physically realistic characteristics of simulation. Using an improved PatchMatch stereomethod to recover images captured real time by a planetary rover navigation camera in a virtual environment provided more complete three-dimensional terrain data for subsequent simulation validation of local path planning. Finally, a simulation environment that combines high-fidelity visual effects and kinematic characteristics supports visualizing the simulation platform: we propose a path planning method using global planning combined with local obstacle avoidance, and we obtain the optimal path that satisfies the kinematic constraints.
{"title":"Vision-Based Virtual Simulation Platform for Planetary Rovers","authors":"Li Yang, Chunxiu Han, Chuankai Liu, Ximing He","doi":"10.2514/1.i011296","DOIUrl":"https://doi.org/10.2514/1.i011296","url":null,"abstract":"In order to evaluate the feasibility of planetary exploration missions, it is imperative to construct planetary terrain environments on the ground. Nevertheless, the implementation of this method is characterized by time-consuming and challenging factors. By contrast, resorting to simulation approaches represents a cost-effective and high-efficiency alternative, which can facilitate the simulation validation of planetary rover exploration missions in an effective manner. In this paper, a modular planet rover simulation platform is proposed; by building and overlaying multiple feature layers corresponding to the surface of the planet, we realize the simulation of high-resolution fine terrain and through adjusting the terrain parameters to meet the needs of different simulated terrain. The experimental results show that we have built a scene to satisfy the requirements of visual effects and physically realistic characteristics of simulation. Using an improved PatchMatch stereomethod to recover images captured real time by a planetary rover navigation camera in a virtual environment provided more complete three-dimensional terrain data for subsequent simulation validation of local path planning. Finally, a simulation environment that combines high-fidelity visual effects and kinematic characteristics supports visualizing the simulation platform: we propose a path planning method using global planning combined with local obstacle avoidance, and we obtain the optimal path that satisfies the kinematic constraints.","PeriodicalId":50260,"journal":{"name":"Journal of Aerospace Information Systems","volume":"51 1","pages":""},"PeriodicalIF":1.5,"publicationDate":"2023-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81052861","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Caleb Wagner, Cecilia Mauceri, Philip Twu, Yuliya Marchetti, J. Russino, Dustin Aguilar, G. Rabideau, S. Tepsuporn, Steve Ankuo Chien, Glenn Reeves
There is a desire for robotic spacecraft to perform exploration in unknown, dynamic environments. The Europa Lander Mission Concept is one such mission that needs to deal with an extremely limited lifetime and energy supply, manage intermittent communications with long blackouts, face numerous environmental dangers, and ultimately take place too far from Earth to rely on human control. No missions to date have operated with the required level of autonomy and under the same level of communication constraints, uncertainty, and mission concept complexity as this mission. As a result, the viability of the autonomy must be demonstrated before it will be trusted with mission-critical planning. In this paper, we present an autonomous software prototype that can demonstrate and test the ability of different planners and executives to carry out complex, science-centric missions with limited interventions from humans. The prototype uses a hierarchical utility model that is used to maximize both the amount of expected science return as well as the number of mission objectives imposed by the ground. We demonstrate how this system handles some of the autonomous tasks expected of complex space missions such as decision making, in-situ data acquisition and analysis, data prioritization, resource management, and failure response handling in both simulation and on actual hardware. Through several scenario-based experiments we show how different planners and executives can meet the challenges of the Europa Lander Mission Concept. We also demonstrate that this system can be used in concert with a hardware prototype for autonomy field tests.
{"title":"Demonstrating Autonomy for Complex Space Missions: A Europa Lander Mission Autonomy Prototype","authors":"Caleb Wagner, Cecilia Mauceri, Philip Twu, Yuliya Marchetti, J. Russino, Dustin Aguilar, G. Rabideau, S. Tepsuporn, Steve Ankuo Chien, Glenn Reeves","doi":"10.2514/1.i011294","DOIUrl":"https://doi.org/10.2514/1.i011294","url":null,"abstract":"There is a desire for robotic spacecraft to perform exploration in unknown, dynamic environments. The Europa Lander Mission Concept is one such mission that needs to deal with an extremely limited lifetime and energy supply, manage intermittent communications with long blackouts, face numerous environmental dangers, and ultimately take place too far from Earth to rely on human control. No missions to date have operated with the required level of autonomy and under the same level of communication constraints, uncertainty, and mission concept complexity as this mission. As a result, the viability of the autonomy must be demonstrated before it will be trusted with mission-critical planning. In this paper, we present an autonomous software prototype that can demonstrate and test the ability of different planners and executives to carry out complex, science-centric missions with limited interventions from humans. The prototype uses a hierarchical utility model that is used to maximize both the amount of expected science return as well as the number of mission objectives imposed by the ground. We demonstrate how this system handles some of the autonomous tasks expected of complex space missions such as decision making, in-situ data acquisition and analysis, data prioritization, resource management, and failure response handling in both simulation and on actual hardware. Through several scenario-based experiments we show how different planners and executives can meet the challenges of the Europa Lander Mission Concept. We also demonstrate that this system can be used in concert with a hardware prototype for autonomy field tests.","PeriodicalId":50260,"journal":{"name":"Journal of Aerospace Information Systems","volume":"3 1","pages":""},"PeriodicalIF":1.5,"publicationDate":"2023-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74431986","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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