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Adaptive Flower Pollination Algorithm-Based Energy Efficient Routing Protocol for Multi-Robot Systems
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DOI：10.1109/ACCESS.2021.3086628.png)
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Abstract
En 中文
The exploration and mapping of unknown environments, where the reliable exchange of data between the robots and the base station (BS) also plays a pivotal role, are some of the fundamental problems of mobile robotics. The maximum energy of a robot is utilized for navigation and communication. The communication between the robots and the BS is limited by the transmission range and the battery capacity. This situation inflicts constraints while designing an effective communication strategy for a multi-robot system (MRS). The biggest challenge lies in designing a unified framework for navigation and communication of the robots. The underlying notion is to utilize the minimum energy for communication (without limiting the range/efficiency of communication) to ensure that the maximum energy can be used for navigation (for larger area coverage). In this work, we present a communication strategy by using adaptive flower pollination optimization algorithm for MRS in conjunction with simultaneous localization and mapping (SLAM) technique for navigation and map making. The proposed strategy has been compared with multiple routing algorithms in terms of network life time and energy efficiency. The proposed strategy performs 4% better compared with harmony search algorithm (HSA) and approximately 10% better compared with distance aware residual energy-efficient stable election protocol (DARE-SEP) in terms of the total network lifetime when 50% of robots are alive. The performance drastically improves by 20% till the last robot is alive compared with HSA and approximately 26% compared with DARE-SEP. Hence, the energy saved during communication with the utilization of proposed strategy helps the robots explore more areas, which ultimately elevates the efficacy of the whole system.
Keywords:
Robots
Robot kinematics
Delays
Routing protocols
Task analysis
Routing
Bandwidth
Area exploration
multi-robot systems
optimization
robot communication
navigation
SLAM
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