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We propose a model predictive control (MPC) approach to solve a flock control problem while incorporating obstacle avoidance capabilities within a leader-follower framework. To achieve this, we utiliz...e the future trajectory prediction calculated by each agent and employ Reynolds’ traditional flocking rules (cohesion, separation, and alignment) as a foundation, which we tailor for navigation purposes rather than formation. We introduce several concepts, including the importance and credibility of information gathered from neighbors, dynamic trade-offs between references, and the fact that near-future predictions are more reliable. We also consider the implicit carriers of educated information, the predominance of cohesion or alignment based on an agent’s distance from its neighbors. These features are integrated into the MPC formulation, and we discuss their benefits through numerical simulations.続きを見る
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