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Extended Capture Point and Optimization-based Control for Quadrupedal Robot Walking on Dynamic Rigid Surfaces ?

机译:延长捕获点和基于优化的QuadrupeDal机器人控制动态刚性表面

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Stabilizing legged robot locomotion on a dynamic rigid surface (DRS) (i.e., rigid surface that moves in the inertial frame) is a complex planning and control problem. The complexity arises due to the hybrid nonlinear walking dynamics subject to explicitly time-varying holonomic constraints caused by the surface movement. The first main contribution of this study is the extension of the capture point from walking on a static surface to locomotion on a DRS as well as the use of the resulting capture point for online motion planning. The second main contribution is a quadratic-programming (QP) based feedback controller design that explicitly considers the DRS movement. The stability and robustness of the proposed control approach are validated through simulations of a quadrupedal robot walking on a DRS with a rocking motion. The simulation results also demonstrate the improved walking performance compared with our previous approach based on offline planning and input-output linearizing control that does not explicitly guarantee the feasibility of ground contact constraints.
机译:稳定在动态刚性表面(DRS)(即,在惯性帧中移动的刚性表面)的腿部机器人机器人是复杂的规划和控制问题。由于混合非线性行走动态的复杂性出现,这是由表面运动引起的明确时变态的定性约束。本研究的第一个主要贡献是捕获点的延伸,从静态表面行走到DRS上的运动以及用于在线运动规划的所产生的捕获点的使用。第二主要贡献是基于二次编程(QP)的反馈控制器设计,明确地考虑了DRS运动。通过在具有摇摆运动的DRS上行走的Quadrupeal机器人的模拟来验证所提出的控制方法的稳定性和稳健性。仿真结果还展示了与我们以前的方法基于离线规划和输入输出线性化控制相比的改进的行走性能,这些方法没有明确保证地接触约束的可行性。

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