论文标题
改编验证合并控制屏障函数的基于控制的控制合成
Adaptation for Validation of a Consolidated Control Barrier Function based Control Synthesis
论文作者
论文摘要
在存在多个控制屏障功能（CBF）约束的情况下，我们开发了一种新型的基于适应的技术，用于安全控制设计。具体而言，我们介绍了一种将任何数量的候选CBF合成的方法中的一个合并的CBF候选者，并提出了其成分权重的参数适应定律，以使合并CBF的可控动力学不变。然后，我们证明，使用适应法可以证明合并的CBF候选人对一类非线性，控制型，多机构系统有效，该系统允许其在基于二次程序的控制法中使用。我们强调了我们在拥挤的仓库环境中对多机器人目标问题进行模拟的方法的成功，并通过AION地面流浪者在实验室中进一步证明了其在实验室中的功效，在其他行为既积极又保守的车辆中。
We develop a novel adaptation-based technique for safe control design in the presence of multiple control barrier function (CBF) constraints. Specifically, we introduce an approach for synthesizing any number of candidate CBFs into one consolidated CBF candidate, and propose a parameter adaptation law for the weights of its constituents such that the controllable dynamics of the consolidated CBF are non-vanishing. We then prove that the use of our adaptation law serves to certify the consolidated CBF candidate as valid for a class of nonlinear, control-affine, multi-agent systems, which permits its use in a quadratic program based control law. We highlight the success of our approach in simulation on a multi-robot goal-reaching problem in a crowded warehouse environment, and further demonstrate its efficacy experimentally in the laboratory via AION ground rovers operating amongst other vehicles behaving both aggressively and conservatively.
