This paper presents a development of a novel path planning algorithm, called Generalized Laser simulator (GLS), for solving the mobilerobot path planning problem in a two-dimensional map with the presence ofconstraint...This paper presents a development of a novel path planning algorithm, called Generalized Laser simulator (GLS), for solving the mobilerobot path planning problem in a two-dimensional map with the presence ofconstraints. This approach gives the possibility to find the path for a wheelmobile robot considering some constraints during the robot movement inboth known and unknown environments. The feasible path is determinedbetween the start and goal positions by generating wave of points in alldirection towards the goal point with adhering to constraints. In simulation,the proposed method has been tested in several working environments withdifferent degrees of complexity. The results demonstrated that the proposedmethod is able to generate efficiently an optimal collision-free path. Moreover,the performance of the proposed method was compared with the A-star andlaser simulator (LS) algorithms in terms of path length, computational timeand path smoothness. The results revealed that the proposed method hasshortest path length, less computational time and the best smooth path. Asan average, GLS is faster than A∗ and LS by 7.8 and 5.5 times, respectivelyand presents a path shorter than A∗ and LS by 1.2 and 1.5 times. In orderto verify the performance of the developed method in dealing with constraints, an experimental study was carried out using a Wheeled Mobile Robot(WMR) platform in labs and roads. The experimental work investigates acomplete autonomous WMR path planning in the lab and road environmentsusing a live video streaming. Local maps were built using data from a live video streaming with real-time image processing to detect segments of theanalogous-road in lab or real-road environments. The study shows that theproposed method is able to generate shortest path and best smooth trajectoryfrom start to goal points in comparison with laser simulator.展开更多
Adaptive genetic algorithm A SA GA, a novel algorithm, which can dynamically modify the parameters of Genetic Algorithms in terms of simulated annealing mechanism, is proposed for path planning of loosely coordinated ...Adaptive genetic algorithm A SA GA, a novel algorithm, which can dynamically modify the parameters of Genetic Algorithms in terms of simulated annealing mechanism, is proposed for path planning of loosely coordinated multi robot manipulators. Over the task space of a multi robot, a strategy of decoupled planning is also applied to the evolutionary process, which enables a multi robot to avoid falling into deadlock and calculating of composite C space. Finally, two representative tests are given to validate A SA GA and the strategy of decoupled planning.展开更多
Mobile robot path planning is an important research branch in the field of mobile robots.The main disadvantage of the traditional artificial potential field(APF)method is prone to local minima problems.Improved artifi...Mobile robot path planning is an important research branch in the field of mobile robots.The main disadvantage of the traditional artificial potential field(APF)method is prone to local minima problems.Improved artificial potential field(IAPF)method is presented in this paper to solve the problem in the traditional APF method for robot path planning in different conditions.We introduce the distance between the robot and the target point to the function of the original repulsive force field and change the original direction of the repulsive force to avoid the trap problem caused by the local minimum point.The IAPF method is suitable for mobile robot path planning in the complicated environment.Simulation and experiment results at the robot platform illustrated the superiority of the modified IAPF method.展开更多
基金The authors would like to thank the United Arab Emirates University for funding this work under Start-Up grant[G00003321].
文摘This paper presents a development of a novel path planning algorithm, called Generalized Laser simulator (GLS), for solving the mobilerobot path planning problem in a two-dimensional map with the presence ofconstraints. This approach gives the possibility to find the path for a wheelmobile robot considering some constraints during the robot movement inboth known and unknown environments. The feasible path is determinedbetween the start and goal positions by generating wave of points in alldirection towards the goal point with adhering to constraints. In simulation,the proposed method has been tested in several working environments withdifferent degrees of complexity. The results demonstrated that the proposedmethod is able to generate efficiently an optimal collision-free path. Moreover,the performance of the proposed method was compared with the A-star andlaser simulator (LS) algorithms in terms of path length, computational timeand path smoothness. The results revealed that the proposed method hasshortest path length, less computational time and the best smooth path. Asan average, GLS is faster than A∗ and LS by 7.8 and 5.5 times, respectivelyand presents a path shorter than A∗ and LS by 1.2 and 1.5 times. In orderto verify the performance of the developed method in dealing with constraints, an experimental study was carried out using a Wheeled Mobile Robot(WMR) platform in labs and roads. The experimental work investigates acomplete autonomous WMR path planning in the lab and road environmentsusing a live video streaming. Local maps were built using data from a live video streaming with real-time image processing to detect segments of theanalogous-road in lab or real-road environments. The study shows that theproposed method is able to generate shortest path and best smooth trajectoryfrom start to goal points in comparison with laser simulator.
文摘Adaptive genetic algorithm A SA GA, a novel algorithm, which can dynamically modify the parameters of Genetic Algorithms in terms of simulated annealing mechanism, is proposed for path planning of loosely coordinated multi robot manipulators. Over the task space of a multi robot, a strategy of decoupled planning is also applied to the evolutionary process, which enables a multi robot to avoid falling into deadlock and calculating of composite C space. Finally, two representative tests are given to validate A SA GA and the strategy of decoupled planning.
基金the National Nature Science Foundation of China(Nos.51579024,61374114)the Fundamental Research Funds for the Central Universities(DMU No.3132016311).
文摘Mobile robot path planning is an important research branch in the field of mobile robots.The main disadvantage of the traditional artificial potential field(APF)method is prone to local minima problems.Improved artificial potential field(IAPF)method is presented in this paper to solve the problem in the traditional APF method for robot path planning in different conditions.We introduce the distance between the robot and the target point to the function of the original repulsive force field and change the original direction of the repulsive force to avoid the trap problem caused by the local minimum point.The IAPF method is suitable for mobile robot path planning in the complicated environment.Simulation and experiment results at the robot platform illustrated the superiority of the modified IAPF method.
