This paper presents redundancy resolution and disturbance rejection via torque optimization in Hybrid Cable-Driven Robots (HCDRs). To begin with, we initiate a redundant HCDR for nonlinear whole-body system modeling and model reduction. Based on the reduced dynamic model, two new methods are proposed to solve the redundancy resolution problem: joint-space torque optimization for actuated joints (TOAJ) and joint-space torque optimization for actuated and unactuated joints (TOAUJ), and they can be extended to other HCDRs. Compared to the existing approaches, this paper provides the first solution (TOAUJ-based method) for HCDRs that can solve the redundancy resolution problem as well as disturbance rejection. Additionally, this paper develops detailed algorithms targeting TOAJ and TOAUJ implementation. A simple yet effective controller is designed for generated data analysis and validation. Case studies are conducted to evaluate the performance of TOAJ and TOAUJ, and the results suggest the effectiveness of the aforementioned approaches.
翻译:本文介绍了通过混合可燃机器人(HCDR)的电磁优化处理冗余和扰动排斥。 首先,我们为非线性全机系统建模和减少模型启动了一个冗余的HCDR。根据减少的动态模型,提出了解决冗余解决方案的两种新方法:为激活联合(TOAJ)和为激活和未激活联合(TOAJ)联合优化联合(TOAJ)和为激活和未激活联合(TOAJ)优化联合空间优化(MOAJ),这些方法可以推广到其他HCDR。与现有方法相比,本文件为HCDR提供了第一个解决方案(基于TOAGJ的方法),能够解决冗余解问题和拒绝扰动。此外,本文件还针对TOAJ和TOAGJ的实施制定了详细的算法。为生成数据分析和验证设计了一个简单而有效的控制器。进行了案例研究,以评价TOAJ和TOGBJ的绩效,结果表明上述方法的有效性。