The Experts below are selected from a list of 9603 Experts worldwide ranked by ideXlab platform
Mary L. Ml Cummings - One of the best experts on this subject based on the ideXlab platform.
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Effects of Safety Protocols on Unmanned Vehicle Ground Operations
Journal of Aerospace Information Systems, 2015Co-Authors: Jason C. Ryan, Mary L. Ml CummingsAbstract:Recent advances in Unmanned and autonomous Vehicle technology are accelerating the push to integrate these Vehicles into human-centered environments such as commercial aviation and public roads. Much of the current research into autonomous systems examines improving the performance of individual Unmanned Vehicles or improving the safety of their interactions with individual humans; very little examines the behavior of the broader system. For large-scale transportation systems, real-world field trials involving Unmanned Vehicles are difficult to execute due to concerns of cost, feasibility of construction, and the maturity of the technologies. This paper describes the use of an agent-based model of Unmanned Vehicle behavior in human-centered environments to explore the effects of their implementation in these domains. In particular, this work explores how safety protocols governing the integration of manned and Unmanned Vehicles affect performance in an aircraft carrier ground control environment. Three different types of futuristic Unmanned Vehicle control architectures are considered in conjunction with four different types of safety protocols: dynamic, area, temporal, and combined area-plus-temporal separation. Results demonstrate that measures of safety vary widely across these systems, demonstrating distinct tradeoffs of safety and mission performance, as well as across different safety measures.
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Operator Objective Function Guidance for a Real-Time Unmanned Vehicle Scheduling Algorithm
Journal of Aerospace Computing, Information, and Communication, 2012Co-Authors: Anthony S. Clare, Andrew K. Whitten, Mary L. Ml Cummings, Jonathan P. How, Olivier ToupetAbstract:Advances in autonomy have made it possible to invert the typical operator-to-Unmanned-Vehicle ratio so that a single operator can now control multiple heterogeneous Unmanned Vehicles. Algorithms used in Unmanned-Vehicle path planning and task allocation typically have an objective function that only takes into account variables initially identified by designers with set weightings. This can make the algorithm seemingly opaque to an operator and brittle under changing mission priorities. To address these issues, it is proposed that allowing operators to dynamically modify objective function weightings of an automated planner during a mission can have performance benefits. A multiple-Unmanned-Vehicle simulation test bed was modified so that operators could either choose one variable or choose any combination of equally weighted variables for the automated planner to use in evaluating mission plans. Results from a human-participant experiment showed that operators rated their performance and confidence highest when using the dynamic objective function with multiple objectives. Allowing operators to adjust multiple objectives resulted in enhanced situational awareness, increased spare mental capacity, fewer interventions to modify the objective function, and no significant differences in mission performance. Adding this form of flexibility and transparency to automation in future Unmanned Vehicle systems could improve performance, engender operator trust, and reduce errors.
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Task-based interfaces for decentralized multiple Unmanned Vehicle control
AUVSI Unmanned Systems North America Conference 2011, 2011Co-Authors: Anthony S. Clare, Mary L. Ml CummingsAbstract:Enhanced autonomy in Unmanned Vehicles (UV) has given human operators the ability to move from teleoperation to supervisory control of single Vehicles, and now multi-Vehicle coordination. This research seeks to leverage task-based interfaces, where the human operator guides a fleet of decentralized UVs via high-level goals as opposed to individual Vehicle control. In such decentralized control architectures, each Vehicle computes its locally best plan to accomplish the mission goals with shared information. The results of two experiments are described where 62 participants performed multi-UV missions in an existing decentralized multiple Unmanned Vehicle simulation environment under increasing task load. Results suggest that a system which uses a task-based interface and decentralized control algorithms may be robust to task load increases by mitigating operator cognitive overload.
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Modified Cooper Harper Scales for Assessing Unmanned Vehicle Displays
Proceedings of the 10th Performance Metrics for Intelligent Systems Workshop, 2010Co-Authors: Birsen Donmez, Hudson D Graham, Mary L. Ml Cummings, Amy S BrzezinskiAbstract:In Unmanned Vehicle (UV) operations, displays are often the only information link between operators and Vehicles. It is essential these displays present information clearly and efficiently so that operators can interact with the UVs to achieve mission objectives. While there are a variety of metrics to evaluate displays, there is no current standardized methodology for operators to subjectively assess a display?s support and identify specific deficiencies. Such a methodology could improve current displays and ensure that displays under development support operator processes. This report presents a quasisubjective display evaluation tool called the Modified Cooper-Harper for Unmanned Vehicle Displays (MCH-UVD) diagnosis tool. This tool, adapted from the Cooper-Harper aircraft handling scale, allows operators to assess a display, translating their judgments on potential display shortcomings into a number corresponding to a particular deficiency in operator support. The General MCH-UVD can be used to diagnose deficiencies for any UV display, while the Specific MCH-UVD is UV and mission specific in its evaluation of displays. This report presents the General MCH-UVD and provides guidance on how to adapt it to create a Specific MCH-UVD through the use of UV mission taxonomies and a questioning method. A UGV search mission case study provides a how-to guide example for generating a Specific MCH-UVD. The report also presents an experiment conducted to validate the MCH-UVD and assess if a mission-specific version is necessary, or if the general form of the MCH-UVD is sufficient for different UV display evaluation. The report concludes with discussion on how to administer the scale, when a Specific scale is necessary, MCH-UVD diagnosis tool limitations, and future work.
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The Role of Human-Automation Consensus in Multiple Unmanned Vehicle Scheduling
The Journal of the Human Factors and Ergonomics Society, 2010Co-Authors: Mary L. Ml Cummings, Andrew Clare, Anthony S. Clare, Christin HartAbstract:OBJECTIVE: This study examined the impact of increasing automation replanning rates on operator performance and workload when supervising a decentralized network of heterogeneous Unmanned Vehicles. BACKGROUND: Futuristic Unmanned Vehicles systems will invert the operator-to-Vehicle ratio so that one operator can control multiple dissimilar Vehicles connected through a decentralized network. Significant human-automation collaboration will be needed because of automation brittleness, but such collaboration could cause high workload. METHOD: Three increasing levels of replanning were tested on an existing multiple Unmanned Vehicle simulation environment that leverages decentralized algorithms for Vehicle routing and task allocation in conjunction with human supervision. RESULTS: Rapid replanning can cause high operator workload, ultimately resulting in poorer overall system performance. Poor performance was associated with a lack of operator consensus for when to accept the automation's suggested prompts for new plan consideration as well as negative attitudes toward Unmanned aerial Vehicles in general. Participants with video game experience tended to collaborate more with the automation, which resulted in better performance. CONCLUSION: In decentralized Unmanned Vehicle networks, operators who ignore the automation's requests for new plan consideration and impose rapid replans both increase their own workload and reduce the ability of the Vehicle network to operate at its maximum capacity. APPLICATION: These findings have implications for personnel selection and training for futuristic systems involving human collaboration with decentralized algorithms embedded in networks of autonomous systems.
Young-hoon Park - One of the best experts on this subject based on the ideXlab platform.
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The sensor fusion design and performance analysis of Unmanned Vehicle for the tele-operation system
ISIE 2001. 2001 IEEE International Symposium on Industrial Electronics Proceedings (Cat. No.01TH8570), 2001Co-Authors: Jae-heung Shim, Young-hoon ParkAbstract:The subject of this paper is sensor fusion analysis of the tele-operation Unmanned Vehicle. The whole system target is studied in context of a motor control system, algorithms for the high level control of a tele-operation Unmanned Vehicle and integration of driving simulator and Unmanned Vehicle. The master system has a host computer and simulator, the slave system is an electronic Vehicle system. The slave Vehicle system consists of three parts. First, the laser sensor system for keeping the front sensory system and ultrasonic sensor system for keeping the side avoiding collision. Second, the acceleration system and brake control system for longitudinal motion control. Third, the steering control system for lateral motion control. In this research, mechanical and electronic parts are implemented to operate the Unmanned Vehicle as a whole-integrated system. We show the experimental result about fixed brake range test, handling performance and acceleration test. The system integrates a driving simulator and the Unmanned Vehicle.
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The system development of Unmanned Vehicle for the teleoperated system interfaced with driving simulator
Proceedings 2001 ICRA. IEEE International Conference on Robotics and Automation (Cat. No.01CH37164), 2001Co-Authors: Jae-heung Shim, Young-hoon ParkAbstract:The integration of a driving simulator and an Unmanned Vehicle by means of a performance concept is suggested. Autonomous navigation is one of the most difficult research topics, having constraints on mobility and speed, and lack of environmental information. However, many innovations on the Vehicle provide the appropriate automatic control in Vehicle subsystem for reducing human error. The master system has a host computer and simulator and the slave system is electronic Vehicle system. The slave Vehicle system consists of three parts. First, laser sensor system for keeping the front sensory system and ultrasonic sensor system for escaping collision at the side. Second, acceleration system and brake control system for longitudinal motion control. Third, steering control system for lateral motion control. In this research, mechanical and electronic parts are implemented to operate Unmanned Vehicle as a whole-integrated system. Driving simulator has a 6 degree-of-freedom motion-base and 3-channel fixed-based simulator. They are fully interactive, highly realistic and, based on personal computer, can be updated easily. Driving simulator is constituted by a vision system, a sound system, the system for control force loading and the 6-axis Stewart platform for motion base. This paper focuses on the integration of remote controlled Unmanned Vehicle and driving simulator. The Vehicle mainly controlled lateral direction and longitudinal direction with actuators for controlling Vehicle movement and sensors for closed-loop system.
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The system integration of Unmanned Vehicle and driving simulator with sensor fusion system
Conference Documentation International Conference on Multisensor Fusion and Integration for Intelligent Systems. MFI 2001 (Cat. No.01TH8590), 2001Co-Authors: Jae-heung Shim, Young-hoon ParkAbstract:In this paper, the integration of driving simulator and Unmanned Vehicle by means of new concept for better performance is suggested. The master system has host computer and simulator and slave system is electronic Vehicle system. The slave Vehicle system consists of three parts. First, laser sensor system for keeping the front sensory system and ultra sonic sensor system for keeping the side range avoiding collision. Second, acceleration system and brake control system for longitudinal motion control. Third, steering control system for lateral motion control. In this research, mechanical and electronic parts are implemented to operate Unmanned Vehicle as a whole-integrated system. Driving simulator has a 6-DOF motion-base and 3-channel fixed-based simulator They are fully interactive, highly realistic and based on personal computer can be updated easily. Driving simulator is constituted by a image generation system, a sound system, the system for control force loading and the 6-axis Stewart platform for motion base. This paper focuses on the integration of remote controlled Unmanned Vehicle and driving simulator The Vehicle mainly controlled lateral direction and longitudinal direction with actuators for controlling Vehicle movement and sensors for closed-loop system.
Jae-heung Shim - One of the best experts on this subject based on the ideXlab platform.
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The sensor fusion design and performance analysis of Unmanned Vehicle for the tele-operation system
ISIE 2001. 2001 IEEE International Symposium on Industrial Electronics Proceedings (Cat. No.01TH8570), 2001Co-Authors: Jae-heung Shim, Young-hoon ParkAbstract:The subject of this paper is sensor fusion analysis of the tele-operation Unmanned Vehicle. The whole system target is studied in context of a motor control system, algorithms for the high level control of a tele-operation Unmanned Vehicle and integration of driving simulator and Unmanned Vehicle. The master system has a host computer and simulator, the slave system is an electronic Vehicle system. The slave Vehicle system consists of three parts. First, the laser sensor system for keeping the front sensory system and ultrasonic sensor system for keeping the side avoiding collision. Second, the acceleration system and brake control system for longitudinal motion control. Third, the steering control system for lateral motion control. In this research, mechanical and electronic parts are implemented to operate the Unmanned Vehicle as a whole-integrated system. We show the experimental result about fixed brake range test, handling performance and acceleration test. The system integrates a driving simulator and the Unmanned Vehicle.
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The system development of Unmanned Vehicle for the teleoperated system interfaced with driving simulator
Proceedings 2001 ICRA. IEEE International Conference on Robotics and Automation (Cat. No.01CH37164), 2001Co-Authors: Jae-heung Shim, Young-hoon ParkAbstract:The integration of a driving simulator and an Unmanned Vehicle by means of a performance concept is suggested. Autonomous navigation is one of the most difficult research topics, having constraints on mobility and speed, and lack of environmental information. However, many innovations on the Vehicle provide the appropriate automatic control in Vehicle subsystem for reducing human error. The master system has a host computer and simulator and the slave system is electronic Vehicle system. The slave Vehicle system consists of three parts. First, laser sensor system for keeping the front sensory system and ultrasonic sensor system for escaping collision at the side. Second, acceleration system and brake control system for longitudinal motion control. Third, steering control system for lateral motion control. In this research, mechanical and electronic parts are implemented to operate Unmanned Vehicle as a whole-integrated system. Driving simulator has a 6 degree-of-freedom motion-base and 3-channel fixed-based simulator. They are fully interactive, highly realistic and, based on personal computer, can be updated easily. Driving simulator is constituted by a vision system, a sound system, the system for control force loading and the 6-axis Stewart platform for motion base. This paper focuses on the integration of remote controlled Unmanned Vehicle and driving simulator. The Vehicle mainly controlled lateral direction and longitudinal direction with actuators for controlling Vehicle movement and sensors for closed-loop system.
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The system integration of Unmanned Vehicle and driving simulator with sensor fusion system
Conference Documentation International Conference on Multisensor Fusion and Integration for Intelligent Systems. MFI 2001 (Cat. No.01TH8590), 2001Co-Authors: Jae-heung Shim, Young-hoon ParkAbstract:In this paper, the integration of driving simulator and Unmanned Vehicle by means of new concept for better performance is suggested. The master system has host computer and simulator and slave system is electronic Vehicle system. The slave Vehicle system consists of three parts. First, laser sensor system for keeping the front sensory system and ultra sonic sensor system for keeping the side range avoiding collision. Second, acceleration system and brake control system for longitudinal motion control. Third, steering control system for lateral motion control. In this research, mechanical and electronic parts are implemented to operate Unmanned Vehicle as a whole-integrated system. Driving simulator has a 6-DOF motion-base and 3-channel fixed-based simulator They are fully interactive, highly realistic and based on personal computer can be updated easily. Driving simulator is constituted by a image generation system, a sound system, the system for control force loading and the 6-axis Stewart platform for motion base. This paper focuses on the integration of remote controlled Unmanned Vehicle and driving simulator The Vehicle mainly controlled lateral direction and longitudinal direction with actuators for controlling Vehicle movement and sensors for closed-loop system.
Wen-hua Chen - One of the best experts on this subject based on the ideXlab platform.
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ICAC - Moving object tracking in support of Unmanned Vehicle opeartion
2013Co-Authors: Runxiao Ding, Wen-hua ChenAbstract:Multi-target tacking (MTT) has become an increasingly important research topic because of its various applications. One of the most recent and challenging implementations is to use MTT in road traffic so as to achieve autonomy for automotive applications from basic driver assistance level to full automation such as Unmanned Vehicles. This paper presents a scenario of tracking multiple moving objects in a traffic crossroad with an immobile Unmanned Vehicle. We introduce a Reid's based Multiple Hypothesis Tracking (MHT) data association filter to solve the problem of multi-target tracking in a cluttered environment. Murty's algorithm is used to find the M-best solutions in the assignment problem involved in MHT and N-scan pruning scheme is implemented to efficiently reduce the number of redundant hypotheses. Through simulation results it is verified that MHT based MTT technique can be effectively applied in Unmanned Vehicle operation.
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Moving object tracking in support of Unmanned Vehicle opeartion
Automation and Computing (ICAC) 2013 19th International Conference on, 2013Co-Authors: Runxiao Ding, Wen-hua ChenAbstract:Multi-target tacking (MTT) has become an increasingly important research topic because of its various applications. One of the most recent and challenging implementations is to use MTT in road traffic so as to achieve autonomy for automotive applications from basic driver assistance level to full automation such as Unmanned Vehicles. This paper presents a scenario of tracking multiple moving objects in a traffic crossroad with an immobile Unmanned Vehicle. We introduce a Reid's based Multiple Hypothesis Tracking (MHT) data association filter to solve the problem of multi-target tracking in a cluttered environment. Murty's algorithm is used to find the M-best solutions in the assignment problem involved in MHT and N-scan pruning scheme is implemented to efficiently reduce the number of redundant hypotheses. Through simulation results it is verified that MHT based MTT technique can be effectively applied in Unmanned Vehicle operation.
Kie Seon Park - One of the best experts on this subject based on the ideXlab platform.
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H/spl infin/ steering control system for the Unmanned Vehicle
ISIE 2001. 2001 IEEE International Symposium on Industrial Electronics Proceedings (Cat. No.01TH8570), 2001Co-Authors: Kie Seon Park, Seun Gweon JeongAbstract:By using the information obtained from the output of MR (magnetoresistive) sensors for an Unmanned Vehicle driving system, we develop an algorithm that decides the distance and directions between the guideline which is made by a magnet and a Vehicle. To improve the robust tracking properties of the closed loop system, we introduce an H/spl infin/ controller and its application for the Unmanned Vehicle driving system.
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H/sup /spl infin// steering control of an Unmanned Vehicle driving system by the MR sensors
ITSC 2001. 2001 IEEE Intelligent Transportation Systems. Proceedings (Cat. No.01TH8585), 2001Co-Authors: Kie Seon ParkAbstract:By using the information obtained from output of MR (magnetoresistive) sensors for an Unmanned Vehicle driving system, we develop an algorithm that finds the distance and directions between a magnetic guideline and the Vehicle. To improve the robust tracking properties of the closed loop system, we introduce H/sup /spl infin// controller and its application for the Unmanned Vehicle driving system.
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Development of an Unmanned Vehicle driving system by MR sensor
2000 26th Annual Conference of the IEEE Industrial Electronics Society. IECON 2000. 2000 IEEE International Conference on Industrial Electronics Contr, 2000Co-Authors: Kie Seon ParkAbstract:By using the information obtained from output of MR (magneto resistive) sensors for an Unmanned Vehicle system which is used in the local position system, we develop an algorithm that decides the distance and directions between the guide line that is made by a series of magnets and MR sensors of the Vehicle. We propose simple Vehicle dynamics and PD control that can minimize the number of sensors in the Unmanned Vehicle driving system.
