Model predictive control‐based tracking controller for hybrid‐driven underwater legged robot

Guangji Zhang, Weisheng Yan, Rongxin Cui, Feiyu Ma
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Abstract

To address the tracking problem of the hybrid‐driven underwater legged robot, a control strategy is proposed that decomposes the whole tracking control system into two subsystems: body‐level and actuator‐level. The body‐level subsystem uses a central pattern generator (CPG)‐based controller to plan suitable gaits to meet the required heading and the forward velocity, crucial for accurate tracking in underwater environments. The actuators‐level subsystem employs a cooperative approach between the C‐shaped legs and thrusters of the robot. To execute the intended gait while adhering to actuation constraints and the no‐slip requirement, the torques of the legs are calculated by a model predictive control and feedback compensation (MPCF)‐based controller. Simultaneously, the calculation of the thrusters concerns four aspects to keep the legs attached to the ground and maintain the stable locomotion of the robot. Simulations on the ROS‐Gazebo platform verify the mobility of the robot and demonstrate the effectiveness of the proposed CPG‐MPCF strategy.
基于模型预测控制的混合动力水下机器人跟踪控制器
为了解决混合驱动水下腿式机器人的跟踪问题,我们提出了一种控制策略,将整个跟踪控制系统分解为两个子系统:身体级和执行器级。身体级子系统使用基于中央模式发生器(CPG)的控制器来规划合适的步态,以满足所需的航向和前进速度,这对水下环境中的精确跟踪至关重要。执行器级子系统在机器人的 C 形腿和推进器之间采用了一种合作方法。为了在执行预定步态的同时遵守执行约束和无滑动要求,腿部扭矩由基于模型预测控制和反馈补偿(MPCF)的控制器计算。同时,推进器的计算涉及四个方面,以保持腿部贴地,维持机器人的稳定运动。在 ROS-Gazebo 平台上进行的模拟验证了机器人的机动性,并证明了所提出的 CPG-MPCF 策略的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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