Page 1. 2000 Society for Design and Process Science Printed in the United States of America Trans... more Page 1. 2000 Society for Design and Process Science Printed in the United States of America Transactions of the SDPS MARCH 2000,Vol. 4, No. 1, pp. 25-35 A CUTTER MOTION SIMULATION SYSTEM Jacob A. Crossman ...
The Army’s vision of the future for armored and mechanized military structure includes the use of... more The Army’s vision of the future for armored and mechanized military structure includes the use of mixed teams of human and robotic forces on a dynamic and rapidly changing battlefield. Successful implementation of this vision will require autonomous and semi-autonomous robotic forces and a command and control infrastructure that will allow human, robotic, and mixed teams to be controlled quickly and easily. For maximum effectiveness this infrastructure should allow human commanders to control the robot teams in a similar manner to how they command human teams, that is, in the language of the military, not the language of robotic control theory. Furthermore, the human interface for robotic command and control must simplify warfighter tasks and automate processes such that cognitive workload is reduced, situation awareness is enhanced, and situational control is preserved. In this paper we present initial results from ongoing efforts in developing an intelligent user interface for con...
Ieee Transactions on Vehicular Technology, Apr 14, 2000
In this paper, we describe an intelligent signal analysis system employing the wavelet transforma... more In this paper, we describe an intelligent signal analysis system employing the wavelet transformation towards solving vehicle engine diagnosis problems. Vehicle engine diagnosis often involves multiple signal analysis. The developed system first partitions a leading signal into small segments representing physical events or stateds based on wavelet mutli-resolution analysis. Second, by applying the segmentation result of the leading signal to the other signals, the detailed properties of each segment, including inter-signal relationships, are extracted to form a feature vector. Finally a fuzzy intelligent system is used to learn diagnostic features from a training set containing feature vectors extracted from signal segments at various vehicle states. The fuzzy system applies its diagnostic knowledge to classify signals as abnormal or normal. The implementation of the system is described and experiment results are presented.
... transform MoveDiskToPeg(d isa Disk,p isa Peg) ( # Consider if a goal to put disk d on peg p c... more ... transform MoveDiskToPeg(d isa Disk,p isa Peg) ( # Consider if a goal to put disk d on peg p consider-if ( goal<DiskOnPeg>(d, p) ) body ( DiskClearToMoveToPeg(d, p) DiskIsOnPeg(d, other-peg) consider-instead( DiskIsOnPeg(d, other-peg), new<DiskIsOnPeg>(d, p))) ) ...
Abstract Multi-hypothesis, kinematic trackers are the state-of-the-art in automated ground motion... more Abstract Multi-hypothesis, kinematic trackers are the state-of-the-art in automated ground motion target indicator (GMTI) data processing. These systems are not designed to recognize long duration behaviors and under complex conditions these systems often ...
DARPA's Real-time Adversarial Intelligence and Decision-making (RAID) program [1] has demonstrate... more DARPA's Real-time Adversarial Intelligence and Decision-making (RAID) program [1] has demonstrated a promising new capability to predict enemy location and intent in dynamic urban combat environments. This capability may significantly improve the Blue commander's decision processes by increasing his situational awareness and tactical team coordination capabilities. Experimental results obtained over the past two years indicate that a single commander in a simulated urban combat environment assisted by RAID outperforms a 5-person senior staff of military Subject Matter Experts. These results also indicate that RAID predictions and recommendations can improve the mission planning process by providing a previously unavailable level of predictive analysis. This paper will address several team performance factors that are improved by RAID and their impact on the mission planning process, present results from the RAID Experiment 4 (July 2006), and describe a key technology extension that is needed for improving the real-time situational awareness data provided to RAID.
The Army’s vision of the future for armored and mechanized military structure includes the use of... more The Army’s vision of the future for armored and mechanized military structure includes the use of mixed teams of human and robotic forces on a dynamic and rapidly changing battlefield. Successful implementation of this vision will require autonomous and semi-autonomous robotic forces and a command and control infrastructure that will allow human, robotic, and mixed teams to be controlled quickly and easily. For maximum effectiveness this infrastructure should allow human commanders to control the robot teams in a similar manner to how they command human teams, that is, in the language of the military, not the language of robotic control theory. Furthermore, the human interface for robotic command and control must simplify warfighter tasks and automate processes such that cognitive workload is reduced, situation awareness is enhanced, and situational control is preserved. In this paper we present initial results from ongoing efforts in developing an intelligent user interface for con...
Many military applications require the distance information from a moving vehicle to targets in v... more Many military applications require the distance information from a moving vehicle to targets in video image sequences. For indirect driving, lack of perception of depth in view hinders steering and navigation. In this paper we present a real-time depth detection system DepthFinder, a system that finds the distances of objects through a monocular vision model. DepthFinder can be used with
This report describes the High-bevel Symbolic Representation (HLSR) project for the U.S. Air Forc... more This report describes the High-bevel Symbolic Representation (HLSR) project for the U.S. Air Force PRDA 03-01-HE: Human Performance in Modeling and Simulation, Technical Area 2: Opposing Force Behaviors. This report summarizes the work done on Defense Modeling Simulation contract F33615-03-C-6343 to develop a high level symbolic representation (HLSR) for behavior modeling. This effort seeks to increase development efficiency and reuse in behavior modeling. The report describes the development of a high level language that abstracts the details of individual intelligent system architectures (ISA), allowing developers to focus their effort on tasks directly related to producing intelligent behavior. This language is designed to be complied into executable representations on multiple ISAs. This report targets two ISAs, Soar and ACT-R. These ISAs have a proven tract record of generating capable behavior models in many domains. There were three primary goals. First, the desire to constru...
this paper, we present the major features of our Fuzzy Intelligent System including its abilities... more this paper, we present the major features of our Fuzzy Intelligent System including its abilities to automatically formulate rules (learn), accommodate expert knowledge, make diagnostic decisions from test data, and, finally, deal effectively with system uncertainty and data imprecision. The system was developed for use in Windows 9X, NT, 2000. A particular application to detection of vacuum leaks in vehicles is given at the end. Rule Generation: Learning Fuzzy reasoning is performed within the context of a fuzzy system model, which consists of control and solution variables, fuzzy sets, rule (proposition) statements, and an underlying control structure. For our diagnostic problem, the control variables are the known parameters of behavior (e.g. air intake, engine speed, etc), the solution variable(s) are the possible faults (e.g. vacuum leak), and the fuzzy sets consist of values or terms of the control and solution variables (e.g. high, low, medium). The rules describe the system ...
2012 International Conference on Collaboration Technologies and Systems (CTS), 2012
ABSTRACT Typical human-robot interaction (HRI) is through tele-operation or point-and-click inter... more ABSTRACT Typical human-robot interaction (HRI) is through tele-operation or point-and-click interfaces that require extensive training to become proficient and require the user's complete attention to operate. For unmanned platforms to reach their full potential, users must be able to exert supervisory control over those platforms. This requires more effective means of communication in both directions, including high-level commands given to the vehicle and meaningful feedback to the user. Our aim is to reduce the training requirements and workload needed to interact with unmanned systems effectively and to raise the level of user interaction with these systems so that supervisory control is possible. In this paper we describe an intelligent user interface, called the Smart Interaction Device (SID) that facilitates a dialogue between the user and the unmanned platform. SID works with the user to understand the user's intent, including asking any clarification questions. Once an understanding is established, SID translates that intent into the language of the platform. SID also monitors the platform's progress in order to give feedback to the user about status or problems that arise. We have incorporated multiple input modalities, including speech, gesture, and sketch as natural ways for a user to communicate with unmanned platforms. SID also provides multiple modes of feedback, including graphics, video and speech. We describe SID's architecture and some examples of its application in different domains.
In this paper, we describe a multiple Signal Fault Detection system that employs fuzzy logic at t... more In this paper, we describe a multiple Signal Fault Detection system that employs fuzzy logic at two levels of detection: signal segment fault and signal fault. The system involves signal segmentation, feature extraction and fuzzy logic based segment fault detection and signal fault detection. At the signal segment level, we developed a fuzzy learning algorithm that learns from good vehicle signals only. The system has been implemented and tested extensively of vehicle signals. The experiments using vehicle engine Electronic Control Unit(ECU) signals are presented and discussed in the paper.
Proceedings of the International Joint Conference on Neural Networks, 2003., 2003
Absrracf-This paper presents our research in Case-Based Reasoning (CBR) with application to vehic... more Absrracf-This paper presents our research in Case-Based Reasoning (CBR) with application to vehicle fault diagnosis. We have developed a Distributed Diagnostic Agent System, DDAS that detects faults of a device based on signal analysis and machine learning. The CBR techniques presented here are used to find root cause of vehicle faults based on the information provided by the signal agents in DDAS. Two CBR methods are presented, one used directly the diagnostic output from the signal agents and another uses the signal segment features. We present experiments conducted on real vehicle cases collected from auto dealers and the results show that both method are effectiue in finding root causes of vehicle faults.
2009 IEEE Conference on Technologies for Homeland Security, 2009
IEDs, made infamous in Iraq and Afghanistan, are a potential terrorist weapon anywhere in the wor... more IEDs, made infamous in Iraq and Afghanistan, are a potential terrorist weapon anywhere in the world. Most counter-IED technologies are targeted at the point of the blast. DEFUSE can interdict and disrupt OPFOR activities left of the blast, well before planting and detonating the IED. The system integrates three layers of simulation: social, process, and environmental.
As with training for other complex military systems, training Forward Observers to properly deliv... more As with training for other complex military systems, training Forward Observers to properly deliver Indirect Fire calls involves multiple participants and can be expensive to coordinate. One solution to this is to automate aspects of the Call for Fire process to enable a human Forward Observer trainee to train anytime and anywhere, without the need for extra participants. This paper describes an automated Fire Direction Center, responsible for accepting spoken Calls for Fire from a Forward Observer trainee. In this paper, we describe the automation aspects of the Indirect Fire training: the motivation behind the work, the general design of the system, the challenges we faced, and our approach in addressing these challenges.
This paper examines some of the constraints on cognition assumed and imposed by the ACT-R and Soa... more This paper examines some of the constraints on cognition assumed and imposed by the ACT-R and Soar cognitive architectures. In particular, we study how these constraints either encourage or require particular types of "modeling idioms" in the form of programming patterns that commonly appear in implemented models. Because of the nature of the mapping of the architectures to human cognition, each modeling idiom translates relatively directly into changes in model behavior data, such as decision timing, memory access, and error rates. Our analysis notes that both architectures have sometimes adopted extreme and opposed constraints, where the human architecture most likely relies on some mixed or more moderate set of constraints.
Page 1. 2000 Society for Design and Process Science Printed in the United States of America Trans... more Page 1. 2000 Society for Design and Process Science Printed in the United States of America Transactions of the SDPS MARCH 2000,Vol. 4, No. 1, pp. 25-35 A CUTTER MOTION SIMULATION SYSTEM Jacob A. Crossman ...
The Army’s vision of the future for armored and mechanized military structure includes the use of... more The Army’s vision of the future for armored and mechanized military structure includes the use of mixed teams of human and robotic forces on a dynamic and rapidly changing battlefield. Successful implementation of this vision will require autonomous and semi-autonomous robotic forces and a command and control infrastructure that will allow human, robotic, and mixed teams to be controlled quickly and easily. For maximum effectiveness this infrastructure should allow human commanders to control the robot teams in a similar manner to how they command human teams, that is, in the language of the military, not the language of robotic control theory. Furthermore, the human interface for robotic command and control must simplify warfighter tasks and automate processes such that cognitive workload is reduced, situation awareness is enhanced, and situational control is preserved. In this paper we present initial results from ongoing efforts in developing an intelligent user interface for con...
Ieee Transactions on Vehicular Technology, Apr 14, 2000
In this paper, we describe an intelligent signal analysis system employing the wavelet transforma... more In this paper, we describe an intelligent signal analysis system employing the wavelet transformation towards solving vehicle engine diagnosis problems. Vehicle engine diagnosis often involves multiple signal analysis. The developed system first partitions a leading signal into small segments representing physical events or stateds based on wavelet mutli-resolution analysis. Second, by applying the segmentation result of the leading signal to the other signals, the detailed properties of each segment, including inter-signal relationships, are extracted to form a feature vector. Finally a fuzzy intelligent system is used to learn diagnostic features from a training set containing feature vectors extracted from signal segments at various vehicle states. The fuzzy system applies its diagnostic knowledge to classify signals as abnormal or normal. The implementation of the system is described and experiment results are presented.
... transform MoveDiskToPeg(d isa Disk,p isa Peg) ( # Consider if a goal to put disk d on peg p c... more ... transform MoveDiskToPeg(d isa Disk,p isa Peg) ( # Consider if a goal to put disk d on peg p consider-if ( goal<DiskOnPeg>(d, p) ) body ( DiskClearToMoveToPeg(d, p) DiskIsOnPeg(d, other-peg) consider-instead( DiskIsOnPeg(d, other-peg), new<DiskIsOnPeg>(d, p))) ) ...
Abstract Multi-hypothesis, kinematic trackers are the state-of-the-art in automated ground motion... more Abstract Multi-hypothesis, kinematic trackers are the state-of-the-art in automated ground motion target indicator (GMTI) data processing. These systems are not designed to recognize long duration behaviors and under complex conditions these systems often ...
DARPA's Real-time Adversarial Intelligence and Decision-making (RAID) program [1] has demonstrate... more DARPA's Real-time Adversarial Intelligence and Decision-making (RAID) program [1] has demonstrated a promising new capability to predict enemy location and intent in dynamic urban combat environments. This capability may significantly improve the Blue commander's decision processes by increasing his situational awareness and tactical team coordination capabilities. Experimental results obtained over the past two years indicate that a single commander in a simulated urban combat environment assisted by RAID outperforms a 5-person senior staff of military Subject Matter Experts. These results also indicate that RAID predictions and recommendations can improve the mission planning process by providing a previously unavailable level of predictive analysis. This paper will address several team performance factors that are improved by RAID and their impact on the mission planning process, present results from the RAID Experiment 4 (July 2006), and describe a key technology extension that is needed for improving the real-time situational awareness data provided to RAID.
The Army’s vision of the future for armored and mechanized military structure includes the use of... more The Army’s vision of the future for armored and mechanized military structure includes the use of mixed teams of human and robotic forces on a dynamic and rapidly changing battlefield. Successful implementation of this vision will require autonomous and semi-autonomous robotic forces and a command and control infrastructure that will allow human, robotic, and mixed teams to be controlled quickly and easily. For maximum effectiveness this infrastructure should allow human commanders to control the robot teams in a similar manner to how they command human teams, that is, in the language of the military, not the language of robotic control theory. Furthermore, the human interface for robotic command and control must simplify warfighter tasks and automate processes such that cognitive workload is reduced, situation awareness is enhanced, and situational control is preserved. In this paper we present initial results from ongoing efforts in developing an intelligent user interface for con...
Many military applications require the distance information from a moving vehicle to targets in v... more Many military applications require the distance information from a moving vehicle to targets in video image sequences. For indirect driving, lack of perception of depth in view hinders steering and navigation. In this paper we present a real-time depth detection system DepthFinder, a system that finds the distances of objects through a monocular vision model. DepthFinder can be used with
This report describes the High-bevel Symbolic Representation (HLSR) project for the U.S. Air Forc... more This report describes the High-bevel Symbolic Representation (HLSR) project for the U.S. Air Force PRDA 03-01-HE: Human Performance in Modeling and Simulation, Technical Area 2: Opposing Force Behaviors. This report summarizes the work done on Defense Modeling Simulation contract F33615-03-C-6343 to develop a high level symbolic representation (HLSR) for behavior modeling. This effort seeks to increase development efficiency and reuse in behavior modeling. The report describes the development of a high level language that abstracts the details of individual intelligent system architectures (ISA), allowing developers to focus their effort on tasks directly related to producing intelligent behavior. This language is designed to be complied into executable representations on multiple ISAs. This report targets two ISAs, Soar and ACT-R. These ISAs have a proven tract record of generating capable behavior models in many domains. There were three primary goals. First, the desire to constru...
this paper, we present the major features of our Fuzzy Intelligent System including its abilities... more this paper, we present the major features of our Fuzzy Intelligent System including its abilities to automatically formulate rules (learn), accommodate expert knowledge, make diagnostic decisions from test data, and, finally, deal effectively with system uncertainty and data imprecision. The system was developed for use in Windows 9X, NT, 2000. A particular application to detection of vacuum leaks in vehicles is given at the end. Rule Generation: Learning Fuzzy reasoning is performed within the context of a fuzzy system model, which consists of control and solution variables, fuzzy sets, rule (proposition) statements, and an underlying control structure. For our diagnostic problem, the control variables are the known parameters of behavior (e.g. air intake, engine speed, etc), the solution variable(s) are the possible faults (e.g. vacuum leak), and the fuzzy sets consist of values or terms of the control and solution variables (e.g. high, low, medium). The rules describe the system ...
2012 International Conference on Collaboration Technologies and Systems (CTS), 2012
ABSTRACT Typical human-robot interaction (HRI) is through tele-operation or point-and-click inter... more ABSTRACT Typical human-robot interaction (HRI) is through tele-operation or point-and-click interfaces that require extensive training to become proficient and require the user's complete attention to operate. For unmanned platforms to reach their full potential, users must be able to exert supervisory control over those platforms. This requires more effective means of communication in both directions, including high-level commands given to the vehicle and meaningful feedback to the user. Our aim is to reduce the training requirements and workload needed to interact with unmanned systems effectively and to raise the level of user interaction with these systems so that supervisory control is possible. In this paper we describe an intelligent user interface, called the Smart Interaction Device (SID) that facilitates a dialogue between the user and the unmanned platform. SID works with the user to understand the user's intent, including asking any clarification questions. Once an understanding is established, SID translates that intent into the language of the platform. SID also monitors the platform's progress in order to give feedback to the user about status or problems that arise. We have incorporated multiple input modalities, including speech, gesture, and sketch as natural ways for a user to communicate with unmanned platforms. SID also provides multiple modes of feedback, including graphics, video and speech. We describe SID's architecture and some examples of its application in different domains.
In this paper, we describe a multiple Signal Fault Detection system that employs fuzzy logic at t... more In this paper, we describe a multiple Signal Fault Detection system that employs fuzzy logic at two levels of detection: signal segment fault and signal fault. The system involves signal segmentation, feature extraction and fuzzy logic based segment fault detection and signal fault detection. At the signal segment level, we developed a fuzzy learning algorithm that learns from good vehicle signals only. The system has been implemented and tested extensively of vehicle signals. The experiments using vehicle engine Electronic Control Unit(ECU) signals are presented and discussed in the paper.
Proceedings of the International Joint Conference on Neural Networks, 2003., 2003
Absrracf-This paper presents our research in Case-Based Reasoning (CBR) with application to vehic... more Absrracf-This paper presents our research in Case-Based Reasoning (CBR) with application to vehicle fault diagnosis. We have developed a Distributed Diagnostic Agent System, DDAS that detects faults of a device based on signal analysis and machine learning. The CBR techniques presented here are used to find root cause of vehicle faults based on the information provided by the signal agents in DDAS. Two CBR methods are presented, one used directly the diagnostic output from the signal agents and another uses the signal segment features. We present experiments conducted on real vehicle cases collected from auto dealers and the results show that both method are effectiue in finding root causes of vehicle faults.
2009 IEEE Conference on Technologies for Homeland Security, 2009
IEDs, made infamous in Iraq and Afghanistan, are a potential terrorist weapon anywhere in the wor... more IEDs, made infamous in Iraq and Afghanistan, are a potential terrorist weapon anywhere in the world. Most counter-IED technologies are targeted at the point of the blast. DEFUSE can interdict and disrupt OPFOR activities left of the blast, well before planting and detonating the IED. The system integrates three layers of simulation: social, process, and environmental.
As with training for other complex military systems, training Forward Observers to properly deliv... more As with training for other complex military systems, training Forward Observers to properly deliver Indirect Fire calls involves multiple participants and can be expensive to coordinate. One solution to this is to automate aspects of the Call for Fire process to enable a human Forward Observer trainee to train anytime and anywhere, without the need for extra participants. This paper describes an automated Fire Direction Center, responsible for accepting spoken Calls for Fire from a Forward Observer trainee. In this paper, we describe the automation aspects of the Indirect Fire training: the motivation behind the work, the general design of the system, the challenges we faced, and our approach in addressing these challenges.
This paper examines some of the constraints on cognition assumed and imposed by the ACT-R and Soa... more This paper examines some of the constraints on cognition assumed and imposed by the ACT-R and Soar cognitive architectures. In particular, we study how these constraints either encourage or require particular types of "modeling idioms" in the form of programming patterns that commonly appear in implemented models. Because of the nature of the mapping of the architectures to human cognition, each modeling idiom translates relatively directly into changes in model behavior data, such as decision timing, memory access, and error rates. Our analysis notes that both architectures have sometimes adopted extreme and opposed constraints, where the human architecture most likely relies on some mixed or more moderate set of constraints.
Uploads
Papers by Jacob Crossman