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In this paper, we develop an adaptive scheme based on reinforcement learning (RL) for planning the construction tasks using a quadrotor. Moreover, an autonomous construction system to assemble user-specified 3-D structures is proposed. Nowadays, complex construction tasks using mobile robots are characterized by three fundamental problems: assembly planning, motion planning, and path tracking control...
In this paper, we describe a stochastic learning approach for planning of assembly and construction tasks of 3-D structures using multiple quadrotors. A planning framework is proposed to generate different sets of high-level plans for the aerial robots. This architecture demonstrates significant advances in ability to quickly find good solutions for complex construction tasks, considering the real...
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