The Infona portal uses cookies, i.e. strings of text saved by a browser on the user's device. The portal can access those files and use them to remember the user's data, such as their chosen settings (screen view, interface language, etc.), or their login data. By using the Infona portal the user accepts automatic saving and using this information for portal operation purposes. More information on the subject can be found in the Privacy Policy and Terms of Service. By closing this window the user confirms that they have read the information on cookie usage, and they accept the privacy policy and the way cookies are used by the portal. You can change the cookie settings in your browser.
We present a framework for improving adaptability of Learning from Demonstration (LfD) strategy by combining the LfD and Sequential Quadratic Programming (SQP). The advantage of the LfD method is that it can find a motion planning solution that is suitable to a task in a short time. Although the method successfully generates a motion when a query point is similar to learned trajectories, it has a...
Optimization-based methods have been recently proposed to solve motion planning problems with complex constraints. Previous methods have used optimization methods that may converge to a local minimum. In this study, particle swarm optimization (PSO) is proposed for trajectory optimization. PSO is a population-based stochastic global optimization method inspired by group behaviors in wildlife, and...
A diverse path set generation method to solve the two-point boundary value problem is first proposed here. The diverse path set planning algorithm (DPSP) generates the probabilistic roadmap and extracts paths that connect a fixed start and a goal point from the roadmap. The roadmap is revised as the path is extracted. The path set is evaluated by the proposed path set fitness function with respect...
This paper addresses a planning method to generate well distributed multiple paths in a control space. For this purpose, we employ and combine rapidly-exploring random tree (RRT), evolutionary algorithm (EA) to compose a diverse multi-path planning (DMPP) algorithm. A population is composed of individuals which represent a path-set. Each individual includes a predefined number of feasible path generated...
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.