Dynamic Path Following Control of a Ground Ackerman Steering Robot to Avoid a Collision

A novel method is proposed to dynamically control the path following of a ground Ackerman steering robot to avoid a collision.The method consists of collision prediction module,collision avoidance module and global path following module.The elliptic repulsive potential field method（ER-PFM）and the enhanced vector polar histogram method（VPH＋）based on the Ackerman steering model are proposed to predict the collision in a dynamic environment.The collision avoidance is realized by the proposed cost function and speed control law.The global path following process is achieved by pure pursuit.Experiments show that the robot can fulfill the dynamic path following task safely and efficiently using the proposed method.

Dynamic A^*path finding algorithm and 3D lidar based obstacle avoidance strategy for autonomous vehicles

This paper presents a novel dynamic A^*path finding algorithm and 3D lidar based local obstacle avoidance strategy for an autonomous vehicle.3D point cloud data is collected and analyzed in real time.Local obstacles are detected online and a 2D local obstacle grid map is constructed at 10 Hz/s.The A^*path finding algorithm is employed to generate a local path in this local obstacle grid map by considering both the target position and obstacles.The vehicle avoids obstacles under the guidance of the generated local path.Experiment results have shown the effectiveness of the obstacle avoidance navigation algorithm proposed.

Mathematical modeling for dynamic stability of sandwich beam with variable mechanical properties of core

The paper is devoted to mathematical modelling of static and dynamic stability of a simply supported three-layered beam with a metal foam core. Mechanical properties of the core vary along the vertical direction. The field of displacements is for- mulated using the classical broken line hypothesis and the proposed nonlinear hypothesis that generalizes the classical one. Using both hypotheses, the strains are determined as well as the stresses of each layer. The kinetic energy, the elastic strain energy, and the work of load are also determined. The system of equations of motion is derived using Hamilton＇s principle. Finally, the system of three equations is reduced to one equation of motion, in particular, the Mathieu equation. The Bubnov-Galerkin method is used to solve the system of equations of motion, and the Runge-Kutta method is used to solve the second-order differential equation. Numerical calculations are done for the chosen family of beams. The critical loads, unstable regions, angular frequencies of the beam, and the static and dynamic equilibrium paths are calculated analytically and verified numerically. The results of this study are presented in the forms of figures and tables.

Cooperative path planning for multi-AUV in time-varying ocean flows

For low-speed underwater vehicles, the ocean currents has a great influence on them, and the changes in ocean currents is complex and continuous, thus whose impact must be taken into consideration in the path planning. There are still lack of authoritative indicator and method for the cooperating path planning. The calculation of the voyage time is a difficult problem in the time-varying ocean, for the existing methods of the cooperating path planning, the computation time will increase exponentially as the autonomous underwater vehicle（AUV） counts increase, rendering them unfeasible. A collaborative path planning method is presehted for multi-AUV under the influence of time-varying ocean currents based on the dynamic programming algorithm. Each AUV cooperates with the one who has the longest estimated time of sailing, enabling the arrays of AUV to get their common goal in the shortest time with minimum timedifference. At the same time, they could avoid the obstacles along the way to the target. Simulation results show that the proposed method has a promising applicability.

Variable dimensional state space based global path planning for mobile robot

A variable dimensional state space（VDSS） has been proposed to improve the re-planning time when the robotic systems operate in large unknown environments.VDSS is constructed by uniforming lattice state space and grid state space.In VDSS,the lattice state space is only used to construct search space in the local area which is a small circle area near the robot,and grid state space elsewhere.We have tested VDSS with up to 80 indoor and outdoor maps in simulation and on segbot robot platform.Through the simulation and segbot robot experiments,it shows that exploring on VDSS is significantly faster than exploring on lattice state space by Anytime Dynamic A＊（AD＊） planner and VDSS is feasible to be used on robotic systems.

Neuro-fuzzy and model-based motion control for mobile manipulator among dynamic obstacles

This paper focuses on autonomous motion control of a nonholonomic platform with a robotic arm, which is called mobile manipulator. It serves in transportation of loads in imperfectly known industrial environments with unknown dynamic obstacles. A union of both procedures is used to solve the general problems of collision-free motion. The problem of collision-free motion for mobile manipulators has been approached from two directions, Planning and Reactive Control. The dynamic path planning can be used to solve the problem of locomotion of mobile platform, and reactive approaches can be employed to solve the motion planning of the arm. The execution can generate the commands for the servo-systems of the robot so as to follow a given nominal trajectory while reacting in real-time to unexpected events. The execution can be designed as an Adaptive Fuzzy Neural Controller. In real world systems, sensor-based motion control becomes essential to deal with model uncertainties and unexpected obstacles.

Uncertainties of critical temperatures based on higher-order fluctuations of the largest fragment charge

The new signature of liquid-gas phase transition has been well indicated by the higher-order fluctuations of the largest fragment charge,but the uncertainties of critical temperatures based on this signature have not been revealed.This study extracts the critical temperatures of liquid-gas phase transition in nuclear reactions and investigates their uncertainties.Utilizing the isospin-dependent quantum molecular dynamics model in conjunction with the statistical model GEMINI enables us to describe the dynamical path from the initial to the final state.An isotope thermometer and a quantum fluctuation thermometer are employed to extract the nuclear temperature.The higher-order fluctuations of the largest fragment charge and critical temperatures are studied in^(124)Sn+^(120)Sn collisions ranging from 400 to 1000 MeV/nucleon and^(124)Sn+AZ collisions at 600 MeV/nucleon.Observations revealed that the pseudo-critical point is robustly indicated by the higher-order fluctuations of the largest fragment charge.The critical temperatures extracted by the isotope thermometer are relatively consistent,with an uncertainty of 15%,while those obtained by the quantum fluctuation thermometer are heavily influenced by the incident energy and mass number of target nuclei.The excitation energy E∗and bound charge Zbound are used for event-sorting.These two ensembles represent the statistical properties of the initial and final states of the system,respectively.The initial-final correlations of statistical properties might lead to two phenomena.First,the size distribution of the largest fragment at the pseudo-critical point based on the Zbound ensemble is wide,while that based on E∗ensemble exhibits bimodality,which is a typical characteristic in the liquid-gas coexistence of a finite system.Second,the temperature at the pseudo-critical point based on the Zbound ensemble is higher than that based on the E∗ensemble.Furthermore,the projectile-like system exhibits a significant dynamical effect in its evolution path from the initial to final state,closely associated with the fluctuation of critical temperature.

Design and performance evaluation of a parking management system for automated, multi-story and robotic parking structure

Purpose–The purpose of this paper is to present design and performance evaluation through simulation of a parking management system(PMS)for a fully automated,multi-story,puzzle-type and robotic parking structure with the overall objective of minimizing customer wait times while maximizing the space utilization.Design/methodology/approach–The presentation entails development and integration of a complete suite of path planning,elevator scheduling and resource allocation algorithms.The PMS aims to manage multiple concurrent requests,in real time and in a dynamic context,for storage and retrieval of vehicles loaded onto robotic carts for a fully automated,multi-story and driving-free parking structure.The algorithm suite employs the incremental informed search algorithm D*Lite with domain-specific heuristics and the uninformed search algorithm Uniform Cost Search for path search and planning.An optimization methodology based on nested partitions and Genetic algorithm is adapted for scheduling of a group of elevators.The study considered a typical business day scenario in the center of a metropolis.Findings–The simulation study indicates that the proposed design for the PMS is able to serve concurrent storage-retrieval requests representing a wide range of Poisson distributed customer arrival rates in real time while requiring reasonable computing resources under realistic scenarios.The customer waiting times for both storage andretrievalrequestsare withinacceptable bounds,whichare set as nomore than 5min,evenin the presence of up to 100 concurrent storage and retrieval requests.The design is able to accommodate a variety of customer arrival rates and presence of immobilized vehicles which are assumed to be scattered across the floors of the structure to make it possible for deployment in real-time environments.Originality/value–The intelligent system design is novel as the fully automated robotic parking structures are just in the process of being matured from a technology standpoint.

Urban Traffic Information Service Application Grid

Traffic information processing is very complicated because of dynamic, cooperative and distributed features. This paper describes the prototype system version 2.0 of Urban Traffic Information Service Application Grid (UTISAG), which is based on the previous version. In this version, a new architecture and more enhanced services are introduced, The. remarkable characteristic of the new system is providing dynamic information services for travelers by grid technology. Therefore, the key research includes integrating large multi-source traffic data, forecasting route status, simulating regional traffic flow parallelly, and implementing optimum dynamic travel scheme based on massive GPS data.