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.
In this paper, a new solution towards the premature convergence problem in Monte Carlo Localization for global localization under highly symmetrical environments is proposed. The algorithm employs a “standard direction” to allow particles to move so as to rearrange weights, providing better exploration as a result. Therefore, there are higher opportunities for particles to converge to the real robot...
Premature convergence often happens when a Monte Carlo localization (MCL) algorithm tries to localize a robot under highly symmetrical environments. In this paper, we propose a novel method of solving such problem for global localization by incorporating a multi-objective evolutionary approach to resample particles with two objectives, including particle weights and population distribution. By employing...
Robot localization plays an important role in the field of robot navigation. One of the most commonly used localization algorithms is Monte Carlo Localization algorithm (MCL). Unfortunately, the traditional MCL is not reliable all the time in both pose tracking and global localization. Many modified MCL algorithms have been proposed to improve the efficiency and performance, such as improved Monte...
In this paper, we propose a new approach to solve the premature convergence problem in Monte Carlo Localization for global localization, entitled "a mechanism for preventing premature convergence". The algorithm uses a referenced relative vector to rearrange weight for each sample, allowing better exploration of a symmetrical environment, resulting in preventing premature convergence problem...
A robot localization plays an important role in the field of robot navigation. One of the most commonly used localization algorithms is Monte Carlo algorithm. To improve the efficiency of robot localization, many modified algorithms have been proposed, such as Self-Adaptive Monte Carlo algorithm. However, this method requires a lot of storage space and intensive computing, especially in large environments...
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.