Mobile robot localization in quasi‐dynamic environments

Abstract

If you would like to write for this, or any other Emerald publication, then please use our Emerald for Authors service information about how to choose which publication to write for and submission guidelines are available for all. Please visit www.emeraldinsight.com/authors for more information. About Emerald www.emeraldinsight.comEmerald is a global publisher linking research and practice to the benefit of society. The company manages a portfolio of more than 290 journals and over 2,350 books and book series volumes, as well as providing an extensive range of online products and additional customer resources and services.Emerald is both COUNTER 4 and TRANSFER compliant. The organization is a partner of the Committee on Publication Ethics (COPE) and also works with Portico and the LOCKSS initiative for digital archive preservation. AbstractPurpose -The purpose of this paper is to address the online localization of mobile (service) robots in real world dynamic environments. Most of the techniques developed so far have been designed for static environments. What is presented here is a novel technique for mobile robot localization in quasi-dynamic environments. Design/methodology/approach -The proposed approach employs a probability grid map and Baye's filtering techniques. The former is used for representing the possible changes in the surrounding environment which a robot might have to face. Findings -Simulation and experimental results show that this approach has a high degree of robustness by taking into account both sensor and world uncertainty. The methodology has been tested under different environment scenarios where diverse complex objects having different sizes and shapes were used to represent movable and non-movable entities. Practical implications -The results can be applied to diverse robotic systems that need to move in changing indoor environments such as hospitals and places where people might require assistance from autonomous robotic devices. The methodology is fast, efficient and can be used in fast-moving robots, allowing them to perform complex operations such as path planning and navigation in real time. Originality/value -What is proposed here is a novel mobile robot localization approach that enables unmanned vehicles to effectively move in real time and know their current location in dynamic environments. Such an approach consists of two steps: a generation of the probability grid map; and a recursive position estimation methodology employing a variant of the Baye's filter.

Asynchronous demodulation CMOS sensor for object labeling and its application in robotics

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A Mobile Robot Path Planning Using Genetic Algorithm in Static Environment

“…Researchers distinguish between various methods used to solve the path planning problem according to two factors, (1) the environment type (i.e., static or dynamic [5] , 2) the path planning algorithms (i.e., global or local) [3] . The static environment is defined as the environment which doesn't contain any moving objects other than a navigating robot; while the dynamic is the environment which has dynamic moving objects (i.e., human beings, moving machines and moving robots).…”

Improving Human-Machine Interaction for a Powered Wheelchair Driver by Using Variable-Switches and Sensors that Reduce Wheelchair-Veer

“…Problems occur when the wheelchair is driven along sloping ground because casters can swivel in the direction of the slope and gravity can then make the wheelchair turn ("veer"). Several types of system were investigated that could assist a wheelchair user: -modelling of the environment [36][37][38][39], -predicting shape of the terrain in front of the sensor [40,41], -Artificial Intelligence [42][43][44][45][46][47][48][49][50][51][52], -Machine Intelligence [53][54][55][56][57][58][59], -and Path Planning [9,14,25,59,60].…”