A Unified Closed-Loop Motion Planning Approach For An I-AUV In Cluttered Environment With Localization Uncertainty

2019 ◽  
Author(s):  
Huan Yu ◽  
Wenjie Lu ◽  
Dikai Liu
Keyword(s):  
Motion Planning ◽  
Closed Loop ◽  
Cluttered Environment ◽  
Planning Approach ◽  
Localization Uncertainty ◽  
Loop Motion

scholarly journals Motion Planning Approach Considering Localization Uncertainty

2020 ◽  
Vol 69 (6) ◽  
pp. 5983-5994 ◽  
Author(s):  
Antonio Artunedo ◽  
Jorge Villagra ◽  
Jorge Godoy ◽  
Maria Dolores del Castillo
Keyword(s):  
Motion Planning ◽  
Planning Approach ◽  
Localization Uncertainty

scholarly journals Motion planning and feedback control for a unicycle in a way point following task: The VFO approach

2009 ◽  
Vol 19 (4) ◽  
pp. 533-545 ◽  
Author(s):  
Maciej Michałek ◽  
Krzysztof Kozłowski
Keyword(s):  
Feedback Control ◽  
Motion Planning ◽  
Closed Loop ◽  
Initial State ◽  
Field Orientation ◽  
Parametric Synthesis ◽  
Finite Precision ◽  
Planning Strategy ◽  
Directing Effect ◽  
Loop Motion

Motion planning and feedback control for a unicycle in a way point following task: The VFO approachThis paper is devoted to theway point followingmotion task of a unicycle where the motion planning and the closed-loop motion realization stage are considered. Theway point followingtask is determined by the user-defined sequence of way-points which have to be passed by the unicycle with the assumed finite precision. This sequence will take the vehicle from the initial state to the target state in finite time. The motion planning strategy proposed in the paper does not involve any interpolation of way-points leading to simplified task description and its subsequent realization. The motion planning as well as the motion realization stage are based on the Vector-Field-Orientation (VFO) approach applied here to a new task. The unique features of the resultant VFO control system, namely, predictable vehicle transients, fast error convergence, vehicledirecting effecttogether with very simple controller parametric synthesis, may prove to be useful in practically motivated motion tasks.

Closed loop motion planning of cooperating mobile robots using graph connectivity

2008 ◽  
Vol 56 (4) ◽  
pp. 373-384 ◽  
Author(s):  
Guilherme Augusto Silva Pereira ◽  
Vijay Kumar ◽  
Mario Fernando Montenegro Campos
Keyword(s):  
Motion Planning ◽  
Mobile Robots ◽  
Closed Loop ◽  
Graph Connectivity ◽  
Loop Motion

Curvature Aware Motion Planning with Closed-Loop Rapidly-exploring Random Trees

2021 ◽  
Author(s):  
Berend van den Berg ◽  
Bruno Brito ◽  
Mohsen Alirezaei ◽  
Javier Alonso-Mora
Keyword(s):  
Motion Planning ◽  
Closed Loop ◽  
Random Trees ◽  
Rapidly Exploring Random Trees

Efficient Human Motion Planning Using Recursive Dynamics and Optimal Control Techniques

1999 ◽  
Author(s):  
Janzen Lo ◽  
Dimitris Metaxas
Keyword(s):  
Optimal Control ◽  
Motion Planning ◽  
Closed Loop ◽  
High Efficiency ◽  
Human Motion ◽  
Lagrangian Formulation ◽  
Planning Problem ◽  
Tree Structures ◽  
Recursive Dynamics ◽  
Minimum Torque

Abstract We present an efficient optimal control based approach to simulate dynamically correct human movements. We model virtual humans as a kinematic chain consisting of serial, closed-loop, and tree-structures. To overcome the complexity limitations of the classical Lagrangian formulation and to include knowledge from biomechanical studies, we have developed a minimum-torque motion planning method. This new method is based on the use of optimal control theory within a recursive dynamics framework. Our dynamic motion planning methodology achieves high efficiency regardless of the figure topology. As opposed to a Lagrangian formulation, it obviates the need for the reformulation of the dynamic equations for different structured articulated figures. We use a quasi-Newton method based nonlinear programming technique to solve our minimum torque-based human motion planning problem. This method achieves superlinear convergence. We use the screw theoretical method to compute analytically the necessary gradient of the motion and force. This provides a better conditioned optimization computation and allows the robust and efficient implementation of our method. Cubic spline functions have been used to make the search space for an optimal solution finite. We demonstrate the efficacy of our proposed method based on a variety of human motion tasks involving open and closed loop kinematic chains. Our models are built using parameters chosen from an anthropomorphic database. The results demonstrate that our approach generates natural looking and physically correct human motions.

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