Terrain-Following Motion of an Autonomous Agent as Means of Motion Planning in the Unknown Environment

Abramova, I. A.; Latyshev, Simon; Yang, Bíngen

doi:10.2514/6.2012-4481

Cited by 2 publications

(2 citation statements)

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“…Derivation of the equations of motion for the described dynamical system is similar to the one, developed in the authors' earlier work on the control law for autonomous agent navigation by means of terrain-following motion [45][46] .…”

Section: Generation Of Npos Sets and Derivation Of The Equationsmentioning

confidence: 99%

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Algorithm for generation of optimal flight trajectories for cooperative motion of two aircraft in a dynamically changing environment

Abramova

Latyshev

Yang

2013

AIAA Guidance, Navigation, and Control (GNC) Conference

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This article consisders the problem of cooperative motion of two aircraft, Protected Entity and Electronic Attack/ Jammer asset, negotiating a terrain seeded with threat emitters toward the predefined stationary goal. The developed control algorithm utilizes a hybrid approach to navigation and subsequent optimal path generation, supplementing the reactive component with deliberative elements as well as considering kinematic and dynamic constraints of the moving assets. That way common pitfalls such as generating impossible paths, losing the goal, and getting trapped in the local minima are avoided, whereas the necessary ability to react quickly to changes in the environment is ensured. The described approach is based on providing discrete, in predefined intervals (time steps) updates of navigation parameters that include asset's state vector, next possible waypoint cost matrix, and goal vector. Hence, the navigation component is discrete, computed once per time step, while the trajectory generation component is continuous, governed by the continuous equations of motion. Generation of the pair of next waypoints involves constructing waypoint cost matrices for each asset, defining the acceptable pairs and assigning their weights using heuristic function. Selection of waypoint pair minimizes that weight. Asset alignment geometry for successful jamming together with terrain and inter-asset collision avoidance are involved in waypoint cost determination. The developed functionality for rollback and subsequent branching is essential for optimal path generation. Software implementation of the presented control algorithm is discussed. Case studies and system performance analysis is presented.

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Section: Generation Of Npos Sets and Derivation Of The Equationsmentioning

confidence: 99%

“…In order to avoid possible motion reversal, as explained in [45][46] , the motion constraint is formulated using only two coordinate components:…”

Section: Generation Of Npos Sets and Derivation Of The Equationsmentioning

confidence: 99%