An Approximate Voronoi Boundary Network is constructed as the environmental model by way of enlar-ging the obstacle raster. The connectivity of the path network under complex environment is ensured through build-ing t...An Approximate Voronoi Boundary Network is constructed as the environmental model by way of enlar-ging the obstacle raster. The connectivity of the path network under complex environment is ensured through build-ing the second order Approximate Voronoi Boundary Network after adding virtual obstacles at joint-close grids. Thismethod embodies the network structure of the free area of environment with less nodes, so the complexity of pathplanning problem is reduced largely. An optimized path for mobile robot under complex environment is obtainedthrough the Genetic Algorithm based on the elitist rule and re-optimized by using the path-tightening method. Sincethe elitist one has the only authority of crossover, the management of one group becomes simple, which makes forobtaining the optimized path quickly. The Approximate Voronoi Boundary Network has a good tolerance to the im-precise a priori information and the noises of sensors under complex environment. Especially it is robust in dealingwith the local or partial changes, so a small quantity of dynamic obstacles is difficult to alter the overall character ofits connectivity, which means that it can also be adopted in dynamic environment by fusing the local path planning.展开更多
Given two Banach spaces E, F, let B（E, F） be the set of all bounded linear operators from E into F, ∑r the set of all operators of finite rank r in B（E, F）, and ∑r^# the number of path connected components of ∑...Given two Banach spaces E, F, let B（E, F） be the set of all bounded linear operators from E into F, ∑r the set of all operators of finite rank r in B（E, F）, and ∑r^# the number of path connected components of ∑r. It is known that ∑r is a smooth Banach submanifold in B（E,F） with given expression of its tangent space at each A ∈ ∑r. In this paper, the equality ∑r^# = 1 is proved. Consequently, the following theorem is obtained： for any nonnegative integer r,∑r is a smooth and path connected Banach submanifold in B（E, F） with the tangent space TA∑r = {B E B（E,F） ： BN（A） belong to R（A）} at each A ∈ ∑r if dim F = ∞. Note that the routine method can hardly be applied here. So in addition to the nice topological and geometric property of ∑r the method presented in this paper is also interesting. As an application of this result, it is proved that if E = R^n and F = R^m, then ∑r is a smooth and path connected submanifold of B（R^n,R^m） and its dimension is dim ∑r = （m ＋ n）r- r^2 for each r, 0≤r 〈 min{n,m}.展开更多
Planning a reasonable driving path for trucks in mining areas is a key point to improve mining efficiency.In this paper,a path planning method based on Rapidly-exploring Random Tree Star(RRT∗)is proposed,and several o...Planning a reasonable driving path for trucks in mining areas is a key point to improve mining efficiency.In this paper,a path planning method based on Rapidly-exploring Random Tree Star(RRT∗)is proposed,and several optimizations are carried out in the algorithm.Firstly,the selection process of growth target points is optimized.Secondly,the process of selecting the parent node is optimized and a Dubins curve is used to constraint it.Then,the expansion process from tree node to random point is optimized by the gravitational repulsion field method and dynamic step method.In the obstacle detection process,Dubins curve constraint is used,and the bidirectional RRT∗algorithm is adopted to speed up the iteration of the algorithm.After that,the obtained paths are smoothed by using the greedy algorithm and cubic B-spline interpolation.In addition,to verify the superiority and correctness of the algorithm,an unmanned mining vehicle kinematic model in the form of frontwheel steering is developed based on the Ackermann steering principle and simulated for CoppeliaSim.In the simulation,the Stanley algorithm is used for path tracking and Reeds-Shepp curve to adjust the final parking attitude of the truck.Finally,the experimental comparison shows that the improved bidirectional RRT∗algorithm performs well in the simulation experiment,and outperforms the common RRT∗algorithm in various aspects.展开更多
As autonomous underwater vehicles(AUVs)merely adopt the inductive obstacle avoidance mechanism to avoid collisions with underwater obstacles,path planners for underwater robots should consider the poor search efficien...As autonomous underwater vehicles(AUVs)merely adopt the inductive obstacle avoidance mechanism to avoid collisions with underwater obstacles,path planners for underwater robots should consider the poor search efficiency and inadequate collision-avoidance ability.To overcome these problems,a specific two-player path planner based on an improved algorithm is designed.First,by combing the artificial attractive field(AAF)of artificial potential field(APF)approach with the random rapidly exploring tree(RRT)algorithm,an improved AAF-RRT algorithm with a changing attractive force proportional to the Euler distance between the point to be extended and the goal point is proposed.Second,a twolayer path planner is designed with path smoothing,which combines global planning and local planning.Finally,as verified by the simulations,the improved AAF-RRT algorithm has the strongest searching ability and the ability to cross the narrow passage among the studied three algorithms,which are the basic RRT algorithm,the common AAF-RRT algorithm,and the improved AAF-RRT algorithm.Moreover,the two-layer path planner can plan a global and optimal path for AUVs if a sudden obstacle is added to the simulation environment.展开更多
In order to improve the battle effectiveness of the unmanned aerial vehicle （UAV） under the increasingly complex threat environment, a three-dimension path planning method based on an A ＊ al- gorithm is proposed an...In order to improve the battle effectiveness of the unmanned aerial vehicle （UAV） under the increasingly complex threat environment, a three-dimension path planning method based on an A ＊ al- gorithm is proposed and simulated in this paper which makes the UAV satisfy requirements of different missions. At first, the digital map information is processed vdth an integrated terrain smoothing algorithm, and a safe flight surface which integrates the vehicle dynamic is built and added on the terrain, and then, models of the complicated threats are established and integrated into the digital terrain. At last, an improved A ＊ algorithm is used to plan the three-dimension path on the safe sur- face, and then smooth the path. Simulation results indicate that the approach has a good perform- ance in creating an optimal path in the three-dimension environment and the path planning algorithm is more simple, efficient and easily realized in the engineering field.展开更多
In the real-world situation,the lunar missions’scale and terrain are different according to various operational regions or worksheets,which requests a more flexible and efficient algorithm to generate task paths.A mu...In the real-world situation,the lunar missions’scale and terrain are different according to various operational regions or worksheets,which requests a more flexible and efficient algorithm to generate task paths.A multi-scale ant colony planning method for the lunar robot is designed to meet the requirements of large scale and complex terrain in lunar space.In the algorithm,the actual lunar surface image is meshed into a gird map,the path planning algorithm is modeled on it,and then the actual path is projected to the original lunar surface and mission.The classical ant colony planning algorithm is rewritten utilizing a multi-scale method to address the diverse task problem.Moreover,the path smoothness is also considered to reduce the magnitude of the steering angle.Finally,several typical conditions to verify the efficiency and feasibility of the proposed algorithm are presented.展开更多
基金Project (60234030) supported by the National Natural Science Foundation of China
文摘An Approximate Voronoi Boundary Network is constructed as the environmental model by way of enlar-ging the obstacle raster. The connectivity of the path network under complex environment is ensured through build-ing the second order Approximate Voronoi Boundary Network after adding virtual obstacles at joint-close grids. Thismethod embodies the network structure of the free area of environment with less nodes, so the complexity of pathplanning problem is reduced largely. An optimized path for mobile robot under complex environment is obtainedthrough the Genetic Algorithm based on the elitist rule and re-optimized by using the path-tightening method. Sincethe elitist one has the only authority of crossover, the management of one group becomes simple, which makes forobtaining the optimized path quickly. The Approximate Voronoi Boundary Network has a good tolerance to the im-precise a priori information and the noises of sensors under complex environment. Especially it is robust in dealingwith the local or partial changes, so a small quantity of dynamic obstacles is difficult to alter the overall character ofits connectivity, which means that it can also be adopted in dynamic environment by fusing the local path planning.
基金Supported by the National Science Foundation of China (Grant No.10671049 and 10771101).
文摘Given two Banach spaces E, F, let B（E, F） be the set of all bounded linear operators from E into F, ∑r the set of all operators of finite rank r in B（E, F）, and ∑r^# the number of path connected components of ∑r. It is known that ∑r is a smooth Banach submanifold in B（E,F） with given expression of its tangent space at each A ∈ ∑r. In this paper, the equality ∑r^# = 1 is proved. Consequently, the following theorem is obtained： for any nonnegative integer r,∑r is a smooth and path connected Banach submanifold in B（E, F） with the tangent space TA∑r = {B E B（E,F） ： BN（A） belong to R（A）} at each A ∈ ∑r if dim F = ∞. Note that the routine method can hardly be applied here. So in addition to the nice topological and geometric property of ∑r the method presented in this paper is also interesting. As an application of this result, it is proved that if E = R^n and F = R^m, then ∑r is a smooth and path connected submanifold of B（R^n,R^m） and its dimension is dim ∑r = （m ＋ n）r- r^2 for each r, 0≤r 〈 min{n,m}.
文摘Planning a reasonable driving path for trucks in mining areas is a key point to improve mining efficiency.In this paper,a path planning method based on Rapidly-exploring Random Tree Star(RRT∗)is proposed,and several optimizations are carried out in the algorithm.Firstly,the selection process of growth target points is optimized.Secondly,the process of selecting the parent node is optimized and a Dubins curve is used to constraint it.Then,the expansion process from tree node to random point is optimized by the gravitational repulsion field method and dynamic step method.In the obstacle detection process,Dubins curve constraint is used,and the bidirectional RRT∗algorithm is adopted to speed up the iteration of the algorithm.After that,the obtained paths are smoothed by using the greedy algorithm and cubic B-spline interpolation.In addition,to verify the superiority and correctness of the algorithm,an unmanned mining vehicle kinematic model in the form of frontwheel steering is developed based on the Ackermann steering principle and simulated for CoppeliaSim.In the simulation,the Stanley algorithm is used for path tracking and Reeds-Shepp curve to adjust the final parking attitude of the truck.Finally,the experimental comparison shows that the improved bidirectional RRT∗algorithm performs well in the simulation experiment,and outperforms the common RRT∗algorithm in various aspects.
基金Supported by Zhejiang Key R&D Program 558 No.2021C03157the“Construction of a Leading Innovation Team”project by the Hangzhou Munic-559 ipal government,the Startup funding of New-joined PI of Westlake University with Grant No.560(041030150118)the funding support from the Westlake University and Bright Dream Joint In-561 stitute for Intelligent Robotics.
文摘As autonomous underwater vehicles(AUVs)merely adopt the inductive obstacle avoidance mechanism to avoid collisions with underwater obstacles,path planners for underwater robots should consider the poor search efficiency and inadequate collision-avoidance ability.To overcome these problems,a specific two-player path planner based on an improved algorithm is designed.First,by combing the artificial attractive field(AAF)of artificial potential field(APF)approach with the random rapidly exploring tree(RRT)algorithm,an improved AAF-RRT algorithm with a changing attractive force proportional to the Euler distance between the point to be extended and the goal point is proposed.Second,a twolayer path planner is designed with path smoothing,which combines global planning and local planning.Finally,as verified by the simulations,the improved AAF-RRT algorithm has the strongest searching ability and the ability to cross the narrow passage among the studied three algorithms,which are the basic RRT algorithm,the common AAF-RRT algorithm,and the improved AAF-RRT algorithm.Moreover,the two-layer path planner can plan a global and optimal path for AUVs if a sudden obstacle is added to the simulation environment.
文摘In order to improve the battle effectiveness of the unmanned aerial vehicle （UAV） under the increasingly complex threat environment, a three-dimension path planning method based on an A ＊ al- gorithm is proposed and simulated in this paper which makes the UAV satisfy requirements of different missions. At first, the digital map information is processed vdth an integrated terrain smoothing algorithm, and a safe flight surface which integrates the vehicle dynamic is built and added on the terrain, and then, models of the complicated threats are established and integrated into the digital terrain. At last, an improved A ＊ algorithm is used to plan the three-dimension path on the safe sur- face, and then smooth the path. Simulation results indicate that the approach has a good perform- ance in creating an optimal path in the three-dimension environment and the path planning algorithm is more simple, efficient and easily realized in the engineering field.
基金supported by the National Natural Science Foundations of China(No.11772185)Fundamental Research Funds for the Central Universities(No.3072022JC0202)。
文摘In the real-world situation,the lunar missions’scale and terrain are different according to various operational regions or worksheets,which requests a more flexible and efficient algorithm to generate task paths.A multi-scale ant colony planning method for the lunar robot is designed to meet the requirements of large scale and complex terrain in lunar space.In the algorithm,the actual lunar surface image is meshed into a gird map,the path planning algorithm is modeled on it,and then the actual path is projected to the original lunar surface and mission.The classical ant colony planning algorithm is rewritten utilizing a multi-scale method to address the diverse task problem.Moreover,the path smoothness is also considered to reduce the magnitude of the steering angle.Finally,several typical conditions to verify the efficiency and feasibility of the proposed algorithm are presented.
