Timely investigating post-disaster situations to locate survivors and secure hazardous sources is critical,but also very challenging and risky.Despite first responders putting their lives at risk in saving others,huma...Timely investigating post-disaster situations to locate survivors and secure hazardous sources is critical,but also very challenging and risky.Despite first responders putting their lives at risk in saving others,human-physical limits cause delays in response time,resulting in fatality and property damage.In this paper,we proposed and implemented a framework intended for creating collaboration between heterogeneous unmanned vehicles and first responders to make search and rescue operations safer and faster.The framework consists of unmanned aerial vehicles(UAVs),unmanned ground vehicles(UGVs),a cloud-based remote control station(RCS).A light-weight message queuing telemetry transport(MQTT)based communication is adopted for facilitating collaboration between autonomous systems.To effectively work under unfavorable disaster conditions,antenna tracker is developed as a tool to extend network coverage to distant areas,and mobile charging points for the UAVs are also implemented.The proposed framework’s performance is evaluated in terms of end-to-end delay and analyzed using architectural analysis and design language(AADL).Experimental measurements and simulation results show that the adopted communication protocol performs more efficiently than other conventional communication protocols,and the implemented UAV control mechanisms are functioning properly.Several scenarios are implemented to validate the overall effectiveness of the proposed framework and demonstrate possible use cases.展开更多
In this paper, the car-like robot kinematic model trajectory tracking and control problem is revisited by exploring an optimal analytical solution which guarantees the global exponential stability of the tracking erro...In this paper, the car-like robot kinematic model trajectory tracking and control problem is revisited by exploring an optimal analytical solution which guarantees the global exponential stability of the tracking error. The problem is formulated in the form of tracking error optimization in which the quadratic errors of the position, velocity, and acceleration are minimized subject to the rear-wheel car-like robot kinematic model. The input-output linearization technique is employed to transform the nonlinear problem into a linear formulation. By using the variational approach, the analytical solution is obtained, which is guaranteed to be globally exponentially stable and is also appropriate for real-time applications. The simulation results demonstrate the validity of the proposed mechanism in generating an optimal trajectory and control inputs by evaluating the proposed method in an eight-shape tracking scenario.展开更多
基金supported partially by AirForce Research Laboratory,the Office of the Secretary of Defense(OSD)(FA8750-15-2-0116)the National Science Foundation(NSF)(1832110)the National Institute of Aerospace and Langley(C16-2B00-NCAT)。
文摘Timely investigating post-disaster situations to locate survivors and secure hazardous sources is critical,but also very challenging and risky.Despite first responders putting their lives at risk in saving others,human-physical limits cause delays in response time,resulting in fatality and property damage.In this paper,we proposed and implemented a framework intended for creating collaboration between heterogeneous unmanned vehicles and first responders to make search and rescue operations safer and faster.The framework consists of unmanned aerial vehicles(UAVs),unmanned ground vehicles(UGVs),a cloud-based remote control station(RCS).A light-weight message queuing telemetry transport(MQTT)based communication is adopted for facilitating collaboration between autonomous systems.To effectively work under unfavorable disaster conditions,antenna tracker is developed as a tool to extend network coverage to distant areas,and mobile charging points for the UAVs are also implemented.The proposed framework’s performance is evaluated in terms of end-to-end delay and analyzed using architectural analysis and design language(AADL).Experimental measurements and simulation results show that the adopted communication protocol performs more efficiently than other conventional communication protocols,and the implemented UAV control mechanisms are functioning properly.Several scenarios are implemented to validate the overall effectiveness of the proposed framework and demonstrate possible use cases.
基金supported by the Air Force Research Laboratory and Office of the Secretary of Defense(OSD)(FA8750-15-2-0116)the US Department of Transportation(USDOT)Research and Innovative Technology Administration(RITA)under University Transportation Center(UTC)Program(DTRT13-G-UTC47)
文摘In this paper, the car-like robot kinematic model trajectory tracking and control problem is revisited by exploring an optimal analytical solution which guarantees the global exponential stability of the tracking error. The problem is formulated in the form of tracking error optimization in which the quadratic errors of the position, velocity, and acceleration are minimized subject to the rear-wheel car-like robot kinematic model. The input-output linearization technique is employed to transform the nonlinear problem into a linear formulation. By using the variational approach, the analytical solution is obtained, which is guaranteed to be globally exponentially stable and is also appropriate for real-time applications. The simulation results demonstrate the validity of the proposed mechanism in generating an optimal trajectory and control inputs by evaluating the proposed method in an eight-shape tracking scenario.
