Robotic path planning and navigation in intricate environments pose significant challenges in various domains, including search and rescue, agriculture, and various defense applications. There have been various method...
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ISBN:
(纸本)9781510674295;9781510674288
Robotic path planning and navigation in intricate environments pose significant challenges in various domains, including search and rescue, agriculture, and various defense applications. There have been various methods proposed to solve these problems, such as graph-based methodologies. Although the majority of cell decomposition methods lack the capability to develop a near optimal path, we propose a middle point cell decomposition in combination with a biologically inspired optimization algorithm for robot path planning and mapping. The proposed model leverages vertical cell decomposition in combination with an enhanced biologically inspired particle swarm optimization algorithm (ePSO). Vertical cell decomposition is employed as a spatial partitioning technique, segmenting complex environments into vertical cells, each characterized by a simplified geometric representation. To improve the path finding process, we introduce middle points within these cells. In this research, midpoints in the graph are regulated and slid by the developed biologically inspired optimization approach to generate optimal robot trajectories. This method enables the algorithm to approximate complex geometry more accurately and efficiently, facilitating smoother navigation for robotic systems. The primary objective of this study is to develop a comprehensive model for robotic path planning and navigation in complex environments, with a particular focus on enhancing efficiency, adaptability, and robustness. The proposed model is validated through extensive simulations in diverse complex environments. Comparative studies are performed against existing path planning algorithms, demonstrating the effectiveness of our approach in terms of path quality, computational efficiency, and adaptability to changing conditions
Development of sensor technology has led to low power, low cost and small sized distributed wireless sensor networks (WSN). The self organizable and distributed characteristics of wireless sensor networks had made it ...
详细信息
ISBN:
(纸本)9788132225294;9788132225287
Development of sensor technology has led to low power, low cost and small sized distributed wireless sensor networks (WSN). The self organizable and distributed characteristics of wireless sensor networks had made it for monitoring and control applications at home and other environment. In most of these applications location information plays a crucial role in increasing the performance and reliability of the network. This paper makes an attempt in analyzing and implementation of a novel nature based algorithm known as firefly localization algorithm. This is a distributed algorithm which uses range based trilateration method for distance measurement required for estimating the location of the sensor node. The algorithm is simple to implement and has better convergence and accuracy.
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