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Aiming at the lack of stability and slow convergence of rapidly random-exploring trees (RRT) algorithm, an improved RRT path planning algorithm is proposed. Firstly, based on bidirectional search path planning algorithm, an improved combination strategy is proposed. The combination strategy combines target point search strategy with random search strategy, which not only improve the efficiency of...
This paper solves the problem of computing the best grasp in a discrete point set based on a popular grasp quality measure, namely the largest origin-centered ball contained in the grasp wrench set. So far, the solution to this problem is very limited. Noticing that the quality measure for a grasp is equal to the minimum value of the support function of its grasp wrench set over all directions and...
In this paper, we propose a learning algorithm that speeds up the search in task and motion planning problems. Our algorithm proposes solutions to three different challenges that arise in learning to improve planning efficiency: what to predict, how to represent a planning problem instance, and how to transfer knowledge from one problem instance to another. We propose a method that predicts constraints...
Computer has been widely used and fully researched along with the progress of electronic technology. We are no longer satisfied with simple calculation in computer application, but expect they can replace the human brain to accomplish complex work. So the artificial intelligence has emerged. There is a very classic research topic in the history of artificial intelligence — Intelligent Planning. IJCAI...
Solutions to robotic manipulation problems can be substantially improved through integrated task and motion planning. Existing approaches typically focus on satisfaction, finding a feasible solution, instead of optimization. We formulate large-scale robotic manipulation problems as multi-level optimization, incorporating task, action, and motion planning. We develop an integrated planning approach...
This paper presents an action guided constraint satisfaction technique for planning problem. Different from the standard algorithms which are almost domain independence and cannot reflect the characteristics of the planning progress, we discuss how the action rules in planning act in constraint satisfaction problems. Based on the conclusion, an action directed constraint is proposed to guide the variable...
To play the biggest advantage of unmanned aerial vehicle (UAV), avoiding bunkers and other obstacles, UAV need precision attack at a specific angle into the target in the attack phase. This paper presents a model based on two-sided search for UAV path planning, from the starting point and target point to begin the search to address with the path planning issues with specified target angles and threat...
One of the most popular algorithms in the field of domain independent planning is POP - partial order planning. POP considers a least commitment strategy to solve planning problems. Such strategy delays commitments during the planning phase until it is absolutely necessary. In consequence, the algorithm provides greater flexibility for solving planning problems, but with a higher cost in performance...
GIS geoprocessing service is the inevitable result of the combination of Geographical Information System and Web service technology, which is widely used for the interoperating of geoprocessing operations in distributed platform-independent and language-independent environments. Since function limited single GIS geoprocessing service cannot satisfy the demands of internet users anymore, it is necessary...
The problem of trip planning has received wide concerns in recent years. More and more people require the service of automatically confirming the optimal tour route. When users assign the source and the destination, and the time limit of the tour, how can automatically decide the optimal tour route with the highest sum of the popularity scores of scenic spots. Current methods for trip planning are...
A new category of faster and efficiently planners has been used to solve planning problems, which use heuristic search algorithms to build their plans. One of the first successful planning systems to use this new approach was the Fast Forward (FF) planner, in which many other recent planners have built upon. FF proposed a heuristic function for planning problems and created a strategy that combines...
This paper contributes to the multiagent constraint framework for synthesizing correct local plans and coordination strategies for every participating agent, and meeting their local goals without conflict or blocking. Existing work has focused mainly on developing conflict resolution algorithms for various different types of constraint systems. This paper addresses a new but related problem called...
In this paper, a novel hybrid genetic algorithm is presented for optimization in radiation therapy treatment planning. The proposed Reduced Order Memetic Algorithm (ROMA) is a combination of an evolutionary multi-objective optimization algorithm and gradient-based local search in a reduced order space. The gradient-based optimizer is used for a fast local search and is a variant of the sequential...
This paper describes an efficient stochastic algorithm for planning near-optimal paths for a point agent moving through two-dimensional weighted-region terrain from a specified start point to a specified goal point. Weighted-region terrain consists of polygonal regions with a constant traversal cost within each region, and models differences in vegetation and terrain that affect traversal. Our algorithm...
Digital Interactive Storytelling (DIS) is a relatively new field of interactive computer entertainment which aims at creating interactive applications capable of generating consistent and rich narratives. Planning systems are the most widely used techniques for DIS, however there have not been much novel solutions for DIS research with respect to developing new planning algorithms. Not only no DIS...
To deal with reactive power optimization problem, an adaptive Niche Particle Swarm Optimization algorithm (ANPSO) is presented. Differential Evolution algorithm (DE) is easy to use and has the advantages of strong robustness, but its efficiency is limited and probably to fall into local optimum because the population loss of diversity after several generations. ANDE introduces niche-sharing mechanisms...
With the number of available Web services is rapidly increasing, how to compose multiple Web services automatically to fulfill a given request has attracted much attention. This paper proposes a dedicated planner named AWSP (Automatic Web Service Planner) toward this problem. Compared with other AI planners for automatic Web service composition, AWSP is characterized by its two different heuristic...
The modern state of the art planners are highly effective and has strong handing capability, but most of them can't learn anything from previous experiences. In the past there have been many researches on learning problem in planning and make some progress. However, the knowledge used in these methods is not easy to learn and use such that Learning can often make performance degrade, learning did...
In this paper, we propose a new cooperative algorithm based on tabu search (TS) and genetic algorithm (GA) in order to solve the global planning problem of Universal Mobile Telecommunications System (UMTS) networks. This problem has been shown to be NP-hard as it is composed of three different subproblems (each one being NP-hard): the cell planning problem, the access network planning problem and...
This paper focuses on route planning, especially for unmanned aircrafts in marine environment. Firstly, new heuristic information is adopted such as threat-zone, turn maneuver and forbid-zone based on voyage heuristic information. Then, the cost function is normalized to obtain more flexible and reasonable routes. Finally, an improved sparse A* search algorithm is employed to enhance the planning...
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