Tensor Field guidance for time-based waypoint arrival of UAVs by 4D trajectory generation

Degen, Shane C.; Alvarez, Luis Mejias; Ford, Jason; Walker, Rodney A.

doi:10.1109/aero.2009.4839605

Cited by 17 publications

(6 citation statements)

References 11 publications

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“…After planning waypoints, paths are planned by combinations of straight and circular segments in most cases. Nelson et al suggested the combinations in [21]. Three types were proposed, and their purposes were to preserve equal path lengths, for flying through the waypoints, and minimizing the path lengths.…”

Section: Strategies For Waypoint Flightmentioning

confidence: 98%

“…They focused on wind disturbance due to the wild environment of the Polar Regions; therefore, they used concepts of a vector field and sliding mode control simultaneously to increase the path following performance. Degen et al extended the concept of a vector field into a tensor field [21]. Typical vector field guidance doesn't consider arrival time; however, they included time information in a vector field to satisfy an arrival time constraint with the dimension extended.…”

Section: Bhatia Et Al Designed a Controller For Commercial Autopilotmentioning

confidence: 99%

“…Therefore, the difference between d χ from (3) and (14) is always smaller than 90deg. Hence, the turning radius is added for extra distance as seen in Fig.. Therefore the appropriate r p can be determined by 21 2 max max…”

Section: B Straight Path Following and Arrival Angle Controlmentioning

confidence: 99%

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Vector field guidance for path following and arrival angle control

Lim

Jung

Bang

2014

2014 International Conference on Unmanned Aircraft Systems (ICUAS)

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This paper focuses on unmanned aircraft guidance laws for a straight path and a circular orbit following using the vector field approach. The vector fields introduced in this paper can be applied to not only path following, but also other purposes such as arrival position, angle, and time control. Therefore, they could be applied to various missions providing advantages over other previous vector fields. Stability and performance of the path following has been proved and analyzed using the classical control theory. And simulation using a six degrees-of-freedom aircraft model shows that these guidance laws are effective for the missions even under the existence of wind disturbance.Index Terms-Vector field, vector field guidance, path following, trajectory tracking, arrival angle control, unmanned aircraft (UA), unmanned aerial vehicle (UAV).

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Section: Strategies For Waypoint Flightmentioning

confidence: 98%

Section: Bhatia Et Al Designed a Controller For Commercial Autopilotmentioning

confidence: 99%

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Vector field guidance for path following and arrival angle control

Lim

Jung

Bang

2014

2014 International Conference on Unmanned Aircraft Systems (ICUAS)

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“…Inertial measurement unit (IMU) signal generators have been used in numerous engineering fields for algorithm testing and verification to reduce experimental costs and shorten developing time under laboratory conditions. It can be used in industrial robots for motion control [ 1 , 2 , 3 ], path planning of unmanned aerial vehicles (UAV) [ 4 ], tightly coupled integrated navigation research [ 5 , 6 , 7 ] and guidance system simulation [ 8 ]. A Global Navigation Satellite System (GNSS) signal simulator is required to generate multiple synchronous signals, one for each satellite in view, and to generate consistent navigation data for the receiver to be able to compute the position.…”

Section: Introductionmentioning

confidence: 99%

IMU Signal Generator Based on Dual Quaternion Interpolation for Integration Simulation

Liu

Tang

et al. 2018

Sensors

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This paper focuses on the problem of high-update-rate and high accuracy inertial measurement unit signal generation. In order to be in accordance with the vehicle’s kinematic and dynamic characteristics as well as the characteristics of pseudorange of post-processed global navigation satellite system and their rate measurements, a novel dual quaternion interpolation and analytic integration algorithm based on actual flight data is proposed. The proposed method can simplify the piecewise analytical expressions of angular rates, angular increments and specific force integral increments. Norm corrections are adopted as constraint conditions to guarantee the accuracy of the signals. Numerical simulations are conducted to validate the method’s performance.

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“…As the trajectories for aerobuses are often retrieved from the flight database and planned long in advance, they are inappropriate for UAVs to cope with complex missions and online replanning. The existing 4D trajectory generation methods in UAV fields include tensor field guidance [3], the Bezier polynomial function [4], the method based on the one-at-a-time strategy [5] and the Multistep A* algorithm [6]. However, to meet the arrival time, many approaches adopt speed assignments after planning flyable 3D trajectories.…”

Section: Introductionmentioning

confidence: 99%

Decentralized 4D Trajectory Generation for UAVs Based on Improved Intrinsic Tau Guidance Strategy

Yang

Fang

2016

International Journal of Advanced Robotic Systems

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A decentralized four-dimensional (4D) trajectory generation method for unmanned aerial vehicles (UAVs), which uses the improved intrinsic tau gravity (tau-G) guidance strategy, is presented in this paper. Based on general tau theory, the current tau-G strategy can only generate the 4D trajectory with zero initial and final velocities, which is not appropriate for decentralized applications. By adding an initial velocity to the intrinsic movement of tau-G strategy, the improved tau-G strategy can synchronously guide the position and velocity to the desired values at the arrival time. In our decentralized 4D trajectory generation method, the improved tau-G strategy is used to plan the 4D trajectories for UAVs. To deal with environmental uncertainty and communication limitations, the receding horizon optimization driven by both sampling time and conflict events is utilized to renew trajectory parameters continually. The simulation results of challenging time-constrained tasks demonstrate that the proposed method can efficiently provide safer and lower-cost 4D trajectories.

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Tensor Field guidance for time-based waypoint arrival of UAVs by 4D trajectory generation

Cited by 17 publications

References 11 publications

Vector field guidance for path following and arrival angle control

Vector field guidance for path following and arrival angle control

IMU Signal Generator Based on Dual Quaternion Interpolation for Integration Simulation

Decentralized 4D Trajectory Generation for UAVs Based on Improved Intrinsic Tau Guidance Strategy

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