We present the design and experimental validation of source seeking control algorithms for a unicycle mobile robot that is equipped with novel 3D-printed flexible graphene-based piezoresistive airflow sensors. Based solely on a local gradient measurement from the airflow sensors, we propose and analyze a projected gradient ascent algorithm to solve the source seeking problem. In the case of partial sensor failure, we propose a combination of Extremum-Seeking Control with our projected gradient ascent algorithm. For both control laws, we prove the asymptotic convergence of the robot to the source. Numerical simulations were performed to validate the algorithms and experimental validations are presented to demonstrate the efficacy of the proposed methods.

翻译：我们展示了为单周期移动机器人寻找控制算法的来源的设计和实验性验证,该机器人配备了新型的3D打印软式石墨基双向气流感应器。我们仅仅根据空气流传感器的局部梯度测量,提出并分析一个预测的梯度增速算法,以解决源寻求问题。在部分传感器故障的情况下,我们提议将Extremum-Searking 控制与我们预测的梯度增速算法相结合。在这两种控制法中,我们证明机器人与源的无药可治的融合。进行了数值模拟,以验证算法,并提出了实验性验证,以证明拟议方法的有效性。