Formation control gains significant attention in the multi-robot system field as it contributes to a vast range of applications, such as transportation. This letter presents a constrained optimization-based control law for cooperative logistics mission, which consists of rigid shape formation control, group navigation, individual and team obstacle avoidance tasks. These tasks are defined as equality and inequality constraints with different levels of priority. Hierarchical quadratic programming (HQP) approach is used to solve for the optimal solution with an inclusion of velocity limits as inequality constraints to ensure implementation feasibility. Experiment using actual industrial robots is demonstrated in order to validate the theory.

中文翻译：

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基于递阶二次规划的多机器人协作物体运输系统


编队控制在多机器人系统领域受到广泛关注，因为它有助于运输等广泛的应用。这封信提出了一种基于约束优化的协同物流任务控制律，包括刚性形状形成控制、群体导航、个人和团队避障任务。这些任务被定义为具有不同优先级的平等和不平等约束。分层二次规划（HQP）方法用于求解最优解，其中包含速度限制作为不等式约束，以确保实施的可行性。为了验证该理论，使用实际工业机器人进行了实验。