Path Planning Optimization for Driverless Vehicle in Parallel Parking Integrating Radial Basis Function Neural Network

To optimize performances such as continuous curvature, safety, and satisfying curvature constraints of the initial planning path for driverless vehicles in parallel parking, a novel method is proposed to train control points of the Bézier curve using the radial basis function neural network method. Firstly, the composition and working process of an autonomous parking system are analyzed. An experiment concerning parking space detection is conducted using an Arduino intelligent minicar with ultrasonic sensor. Based on the analysis of the parallel parking process of experienced drivers and the idea of simulating a human driver, the initial path is planned via an arc-line-arc three segment composite curve and fitted by a quintic Bézier curve to make up for the discontinuity of curvature. Then, the radial basis function neural network is established, and slopes of points of the initial path are used as input to train and obtain horizontal ordinates of four control points in the middle of the Bézier curve. Finally, simulation experiments are carried out by MATLAB, whereby parallel parking of driverless vehicle is simulated, and the effects of the proposed method are verified. Results show the trained and optimized Bézier curve as a planning path meets the requirements of continuous curvature, safety, and curvature constraints, thus improving the abilities for parallel parking in small parking spaces.

A Path Planning Method for Mobile Robots Based on Fuzzy Firefly Algorithms

Introducction: Mobile Robot is a kind of robot system consisting of sensors, remote control operators and automatic control mobile carriers. It is a product of integrated application of integrated disciplines developed in recent years. In the research of mobile robot related technology, navigation technology is its core, and path planning is an important link and subject of navigation research. Objective: An improved firefly algorithm is proposed for path planning of Mobile Robots in this paper. Methods: In this paper, an improved firefly algorithm is proposed. Compared with traditional firefly algorithm, this algorithm has three main improvements: (1) using Sobol sequence to initialize population; (2) adding dynamic disturbance coefficient to enhance the global search ability of the algorithm; (3) considering the uncertainty of search, the attraction between individuals is strong. Fuzzy control is carried out by setting membership function. Results: The new algorithm takes advantage of the uniformity of Sobol sequence sampling and starts to optimize in a wider range, which makes the initial path of the algorithm longer, but because the new algorithm introduces the dynamic disturbance coefficient and the fuzzy control strategy, the average running time is shorter. Conclusion: In the simulation experiment of mobile robot path planning problem, the improved firefly algorithm proposed in this paper is easier to jump out of local optimum than the traditional firefly algorithm, and has more robust search ability. Discussion: It is obvious from the graph that in 100 iterations, the FaFA algorithm takes advantage of the uniformity of Sobol sequence sampling and starts to optimize in a wider range, which makes the initial path of the algorithm longer, but because the FaFA algorithm introduces the dynamic disturbance coefficient and the fuzzy control strategy, it makes the algorithm able.

Periodic codings of Bratteli-Vershik systems

We develop conditions for the coding of a Bratteli-Vershik system according to initial path segments to be periodic, equivalently for a constructive symbolic recursive scheme corresponding to a cutting and stacking process to produce a periodic sequence. This is a step toward understanding when a Bratteli-Vershik system can be essentially faithfully represented by means of a natural coding as a subshift on a finite alphabet.

Image Morphology-Based Path Generation for High-Speed Pocketing

Pocket milling has long been a popular means for machining pocket features in structural parts and skins in the aviation industry. Recent advanced milling technologies pose new challenges for pocket milling path which existing contour-parallel path generation schemes cannot overcome. For high-speed machining, pocket milling path is desired to be smooth and with no tool retractions during the process, while the path stepover should be kept within a prescribed range to achieve relatively constant cutting load. These geometric constraints are also vital in the application of aircraft skin mirror milling in order to guarantee a correct and consistent thickness signal reception for real-time adjustment of the process. Traditional path optimization based on local modification can only meet a few of these constraints while others are being violated. Therefore, we propose a novel contour-parallel path generation scheme that respects all these process constraints by utilizing the idea of image morphology. The two-step scheme first generates an initial path by propagating from the rectified medial curve of the pocket shape. The initial path is then treated as a binary image being iteratively deformed and projected back into the pocket region via quadratic optimization. Experimental results show that our developed scheme can generate a smooth, tool retraction free and stepover-guaranteed path for various shapes of pocket.

Traversability Assessment and Trajectory Planning of Unmanned Ground Vehicles with Suspension Systems on Rough Terrain

This paper presents a traversability assessment method and a trajectory planning method. They are key features for the navigation of an unmanned ground vehicle (UGV) in a non-planar environment. In this work, a 3D light detection and ranging (LiDAR) sensor is used to obtain the geometric information about a rough terrain surface. For a given SE(2) pose of the vehicle and a specific vehicle model, the SE(3) pose of the vehicle is estimated based on LiDAR points, and then a traversability is computed. The traversability tells the vehicle the effects of its interaction with the rough terrain. Note that the traversability is computed on demand during trajectory planning, so there is not any explicit terrain discretization. The proposed trajectory planner finds an initial path through the non-holonomic A*, which is a modified form of the conventional A* planner. A path is a sequence of poses without timestamps. Then, the initial path is optimized in terms of the traversability, using the method of Lagrange multipliers. The optimization accounts for the model of the vehicle’s suspension system. Therefore, the optimized trajectory is dynamically feasible, and the trajectory tracking error is small. The proposed methods were tested in both the simulation and the real-world experiments. The simulation experiments were conducted in a simulator called Gazebo, which uses a physics engine to compute the vehicle motion. The experiments were conducted in various non-planar experiments. The results indicate that the proposed methods could accurately estimate the SE(3) pose of the vehicle. Besides, the trajectory cost of the proposed planner was lower than the trajectory costs of other state-of-the-art trajectory planners.

LA POBLACIÓN SAN LUIS. EL CONSEJO SUPERIOR DE HABITACIONES OBRERAS, EL “PROYECTO DOMÉSTICO” Y LAS POLÍTICAS DE VIVIENDA EN SANTIAGO DE CHILE (1921-1926)

Este artículo se pregunta por la población San Luis, construida en Santiago por el Consejo Superior de Habitaciones Obreras durante la primera mitad de la década del veinte. ¿Cuáles fueron las principales características de diseño arquitectónico y urbano de dichas casas y su entorno? ¿Cómo ese emprendimiento puede convertirse en un vehículo para comprender las representaciones de la institución respecto a la vivienda higiénica? ¿Cómo era el sector de la ciudaden que se insertó dicho conjunto? Estas tres preguntas apuntan a ser respondidas mediante un estudio de historia urbana que aborda prioritariamente dimensiones de la política y la arquitectura, indagando la trayectoria inicial de una población erigida por el Estado de Chile. ABSTRACT This article will question for the San Luis poblacion, built in Santiago by the Superior Council of Labor Rooms during the first half of the decade of the 1920s. What were the main characteristics of architectural and urban design of these houses and these environment? How that entrepreneurship can become a vehicle for understanding the representations of the institution with respect to the hygienic housing? What was the sector of the city that was inserted? These threequestions to be answered by a study of urban history that addresses priority dimensions of policy and architecture, to investigate the initial path of a poblacion built by the State of Chile.

Second Path Planning for Unmanned Surface Vehicle Considering the Constraint of Motion Performance

When utilizing the traditional path planning method for unmanned surface vehicles (USVs), ‘planning-failure’ is a common phenomenon caused by the inflection points of large curvatures in the planned path, which exceed the performances of USVs. This paper presents a second path planning method (SPP), which is an initial planning path optimization method based on the geometric relationship of the three-point path. First, to describe the motion performance of a USV in conjunction with the limited test data, a method of integral nonlinear least squares identification is proposed to rapidly obtain the motion constraint of the USV merely by employing a zig zag test. It is different from maneuverability identification, which is performed in combination with various tests. Second, the curvature of the planned path is limited according to the motion performance of the USV based on the traditional path planning, and SPP is proposed to make the maximum curvature radius of the optimized path smaller than the rotation curvature radius of the USV. Finally, based on the ‘Dolphin 1’ prototype USV, comparative simulation experiments were carried out. In the experiment, the path directly obtained by the initial path planning and the path optimized by the SPP method were considered as the tracking target path. The artificial potential field method was used as an example for the initial path planning. The experimental results demonstrate that the tracking accuracy of the USV significantly improved after the path optimization using the SPP method.

HybridHAM: A Novel Hybrid Heuristic for Finding Hamiltonian Cycle

Hamiltonian Cycle Problem is one of the most explored combinatorial problems. Being an NP-complete problem, heuristic approaches are found to be more powerful than exponential time exact algorithms. This paper presents an efficient hybrid heuristic that sits in between the complex reliable approaches and simple faster approaches. The proposed algorithm is a combination of greedy, rotational transformation and unreachable vertex heuristics that works in three phases. In the first phase, an initial path is created by using greedy depth first search. This initial path is then extended to a Hamiltonian path in second phase by using rotational transformation and greedy depth first search. Third phase converts the Hamiltonian path into a Hamiltonian cycle by using rotational transformation. The proposed approach could find Hamiltonian cycles from a set of hard graphs collected from the literature, all the Hamiltonian instances (1000 to 5000 vertices) given in TSPLIB, and some instances of FHCP Challenge Set. Moreover, the algorithm has O(n3) worst case time complexity. The performance of the algorithm has been compared with the state-of-the-art algorithms and it was found that HybridHAM outperforms others in terms of running time.