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.

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.