应用于茶叶罐分拣的码垛机器人最优关节空间控制

针对茶叶罐分拣生产线的高效率运动控制,提出一种码垛机器人最优关节控制方法。首先,设计茶叶罐分拣码垛机器人生产线的三维模型,根据拉格朗日方程推导出机器人动力学模型,明确模型的输入输出关系。进而,利用萤火虫算法的寻优优势对码垛机器人进行运动学反解,并引入NUBRS曲线平滑处理经五阶多项式插补的轨迹。最后,设计快速连续非奇异终端滑模控制器来实现关节空间内的高精度轨迹跟踪控制。研究结果表明:与滑模控制和反步法控制相比,本文控制器具有更高的控制性能;萤火虫算法能在0.37 s内求解机器人反向运动学,结合五阶多项式插补法与NUBRS曲线能获得光滑柔顺的参考关节轨迹;本文控制器能有效抑制集总干扰力矩影响,保证机器人关节空间内轨迹跟踪精度。

Optimal joint space control of palletizing robot applied to tea caddy sorting

To simulate the palletizing robot product line for tea caddy sorting, an optimal controller with a fast continuous nonsingular terminal sliding mode control strategy was proposed. After designing a three dimensional model of the product line, the dynamical model of the palletizing robot was deduced through the Lagrangian equation, which was clarified the inputs and outputs of the system. Then, an artificial intelligence algorithm called glowworm swarm optimization algorithm was used for trajectory planning. The fifth order polynomial interpolation method and NUBRS curve were introduced to smooth the trajectories (i.e., referenced trajectories). Furthermore, a fast continuous nonsingular terminal sliding mode control strategy was designed to accelerate the convergence of the state variables in the system, which can improve the trajectory tracking precision in joint space. Lastly, series of simulation cases were conducted to test the proposed method. The results show that the proposed controller had a higher control performance than the sliding mode and backstepping controllers. The glowworm swarm optimization algorithm could help the robot obtain optimal joint trajectories of 0.37 s. The proposed controller could retrain the lumped torques and ensure the trajectory tracking precision in joint space.