Three Dimensional Path Planning Algorithm for Small UAVs Incorporating Existing Dynamic Soaring Heuristics

2012 ◽  
Vol 225 ◽  
pp. 403-408
Author(s):  
Omar Kassim Ariff ◽  
Tiauw Hiong Go ◽  
Surjatin Wiriadidjaja ◽  
Amzari Zhahir
Keyword(s):  
Three Dimensional ◽  
Small Scale ◽  
Exit Point ◽  
Heuristic Model ◽  
Dynamic Soaring ◽  
Aerial Vehicles ◽  
Waypoint Navigation ◽  
Planning Algorithm ◽  
Uninhabited Aerial Vehicles ◽  
Path Planning Algorithm

An area under consideration of improving the mission effectiveness of small-scale, autonomous Uninhabited Aerial Vehicles (UAVs) has been the increase of speed. One method is to incorporate dynamic slope soaring maneuvers as part of the flight path during waypoint navigation. Research into autonomous dynamic soaring capability in small-scale UAVs began with selecting a suitable maneuver heuristic. The output from the heuristic model has then been used to formulate a non-iterative trajectory forming algorithm. By utilizing Dubin’s curves, a viable trajectory can be generated between the exit point of the dynamic soaring maneuver and the next waypoint. The result is a complete, easily implemented three-dimensional autonomous dynamic soaring capability.

Waypoint Navigation of Small-Scale UAV incorporating Dynamic Soaring

2010 ◽  
Vol 64 (1) ◽  
pp. 29-44 ◽  
Author(s):  
O. K. Ariff ◽  
T. H. Go
Keyword(s):  
Trajectory Optimization ◽  
Optimization Techniques ◽  
Small Scale ◽  
Spatial Constraints ◽  
Dynamic Soaring ◽  
Computational Load ◽  
Aerial Vehicles ◽  
Waypoint Navigation ◽  
Contour Following ◽  
Uninhabited Aerial Vehicles

The latest attempts at improving small scale autonomously guided Uninhabited Aerial Vehicles (UAVs) have concentrated around the increase of range and speed. One of these ways is to incorporate dynamic slope soaring manoeuvres as part of the flight path. This is in contrast to most conventional path-planning algorithms where waypoint guidance is merged with terrain avoidance or contour following capability. Additionally, current trajectory optimization techniques are iterative and so have a considerable computational load. The proposed algorithm is based on Dubin's curves, and is therefore optimal by definition. Being non-iterative, it is comparatively a more efficient algorithm. Hence, a key advantage of the proposed technique is that the desired trajectory is generated quickly in real time with minimum computational load while satisfying the spatial constraints of dynamic slope soaring.

scholarly journals A 2D Optimal Path Planning Algorithm for Autonomous Underwater Vehicle Driving in Unknown Underwater Canyons

2021 ◽  
Vol 9 (3) ◽  
pp. 252
Author(s):  
Yushan Sun ◽  
Xiaokun Luo ◽  
Xiangrui Ran ◽  
Guocheng Zhang
Keyword(s):  
Path Planning ◽  
Obstacle Avoidance ◽  
Autonomous Underwater Vehicles ◽  
Optimal Path ◽  
Small Scale ◽  
Target Point ◽  
Safe Driving ◽  
Policy Gradient ◽  
Planning Algorithm ◽  
Path Planning Algorithm

This research aims to solve the safe navigation problem of autonomous underwater vehicles (AUVs) in deep ocean, which is a complex and changeable environment with various mountains. When an AUV reaches the deep sea navigation, it encounters many underwater canyons, and the hard valley walls threaten its safety seriously. To solve the problem on the safe driving of AUV in underwater canyons and address the potential of AUV autonomous obstacle avoidance in uncertain environments, an improved AUV path planning algorithm based on the deep deterministic policy gradient (DDPG) algorithm is proposed in this work. This method refers to an end-to-end path planning algorithm that optimizes the strategy directly. It takes sensor information as input and driving speed and yaw angle as outputs. The path planning algorithm can reach the predetermined target point while avoiding large-scale static obstacles, such as valley walls in the simulated underwater canyon environment, as well as sudden small-scale dynamic obstacles, such as marine life and other vehicles. In addition, this research aims at the multi-objective structure of the obstacle avoidance of path planning, modularized reward function design, and combined artificial potential field method to set continuous rewards. This research also proposes a new algorithm called deep SumTree-deterministic policy gradient algorithm (SumTree-DDPG), which improves the random storage and extraction strategy of DDPG algorithm experience samples. According to the importance of the experience samples, the samples are classified and stored in combination with the SumTree structure, high-quality samples are extracted continuously, and SumTree-DDPG algorithm finally improves the speed of the convergence model. Finally, this research uses Python language to write an underwater canyon simulation environment and builds a deep reinforcement learning simulation platform on a high-performance computer to conduct simulation learning training for AUV. Data simulation verified that the proposed path planning method can guide the under-actuated underwater robot to navigate to the target without colliding with any obstacles. In comparison with the DDPG algorithm, the stability, training’s total reward, and robustness of the improved Sumtree-DDPG algorithm planner in this study are better.

Kinematics of a Novel Single-Loop Under-Actuated Wrist

2012 ◽  
Author(s):  
Raffaele Di Gregorio
Keyword(s):  
Path Planning ◽  
Closed Form ◽  
Nonholonomic Constraint ◽  
Three Dimensional ◽  
Single Loop ◽  
Closed Form Solutions ◽  
Position Analysis ◽  
Tracking Tasks ◽  
Planning Algorithm ◽  
Path Planning Algorithm

A novel type of parallel wrist (PW) is proposed which, differently from previously presented PWs, features a single-loop architecture and only one nonholonomic constraint. Due to the presence of a nonholonomic constraint, the proposed PW type is under-actuated, that is, it is able to control the platform orientation in a three-dimensional workspace by employing only two actuated pairs, one prismatic (P) and the other revolute (R); and it cannot perform tracking tasks. Position analysis and path planning of this novel PW are studied. In particular, all the relevant position analysis problems are solved in closed form, and, based on these closed-form solutions, a path-planning algorithm is built.

Research on Algorithm for Space Weld Reconstruction and Torch Pose Simulation

2014 ◽  
Vol 1049-1050 ◽  
pp. 833-837
Author(s):  
Peng Yang ◽  
Dong Xing Hui ◽  
Zheng Kai ◽  
Li Shu Tian
Keyword(s):  
Coordinate Transformation ◽  
Spline Interpolation ◽  
Three Dimensional ◽  
Automatic Welding ◽  
Control Points ◽  
B Spline ◽  
Spline Curve ◽  
Planning Algorithm ◽  
Control Terminal ◽  
Path Planning Algorithm

A path planning algorithm based on B-spline interpolation techniques was constructed for automatic welding system.The system used a B-spline curve to reconstruct the weld,it was achieved by reversing the control points of B-spline curve through the prescribed date points. The weld posture model was then obtained from the osculating plane and normal plane of B-spline curve. By taking a series coordinate transformation to the weld posture model, the torch posture model based on control terminal was provided.Experiments show that the new algorithm can readily be used for various three-dimensional welding tasks.

A family of skeletons for motion planning and geometric reasoning applications

2011 ◽  
Vol 25 (4) ◽  
pp. 375-392
Author(s):  
Ata A. Eftekharian ◽  
Horea T. Ilieş
Keyword(s):  
Motion Planning ◽  
Medial Axis ◽  
A Priori ◽  
Three Dimensional ◽  
Geometric Reasoning ◽  
Spatial Configurations ◽  
Planning Algorithm ◽  
Logic Operations ◽  
Path Planning Algorithm ◽  
Special Case

AbstractThe task of planning a path between two spatial configurations of an artifact moving among obstacles is an important problem in practically all geometrically intensive applications. Despite the ubiquity of the problem, the existing approaches make specific limiting assumptions about the geometry and mobility of the obstacles, or those of the environment in which the motion of the artifact takes place. We present a strategy to construct a family of paths, or roadmaps, for two- and three-dimensional solids moving in an evolving environment that can undergo drastic topological changes. Our approach is based on a potent paradigm for constructing geometric skeletons that relies on constructive representations of shapes with R-functions that operate on real-valued half-spaces as logic operations. We describe a family of skeletons that have the same homotopy as that of the environment and contains the medial axis as a special case. Of importance, our skeletons can be designed so that they are “attracted to” or “repulsed by” prescribed spatial sites of the environment. Moreover, the R-function formulation suggests the new concept of a medial zone, which can be thought of as a “thick” skeleton with significant applications for motion planning and other geometric reasoning applications. Our approach can handle problems in which the environment is not fully known a priori, and intrinsically supports local and parallel skeleton computations for domains with rigid or evolving boundaries. Furthermore, our path planning algorithm can be implemented in any commercial geometric kernel, and has attractive computational properties. The capability of the proposed technique are explored through several examples designed to simulate highly dynamic environments.

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