基于图模型预测控制的旋转步态控制
Controlling Pivoting Gait using Graph Model Predictive Control
摘要：
枢转步态是一种高效的以相对较小的操纵力操纵大而重的物体的步态，其中机器人迭代地倾斜物体，使其绕顶点旋转，然后将其放下到地板上。然而，由于其本质上的不稳定性，即使有很小的外部干扰，旋转步态也很容易失败。为了解决这个问题，我们提出了一种控制器，通过引入两种步态模式，即，一种是双支撑模式，它可以以较快的速度操纵相对较轻的物体，另一种是四支撑模式，它可以以较慢的速度操纵相对较重的物体。为了控制枢转步态，考虑到这两种步态模式，应用图形模型预测控制。通过根据所施加的外部干扰自适应地切换步态模式，机器人即使在外部干扰施加到物体的情况下也可以稳定地执行枢转步态。
英文摘要：
Pivoting gait is efficient for manipulating a big and heavy object with relatively small manipulating force, in which a robot iteratively tilts the object, rotates it around the vertex, and then puts it down to the floor. However, pivoting gait can easily fail even with a small external disturbance due to its instability in nature. To cope with this problem, we propose a controller to robustly control the object motion during the pivoting gait by introducing two gait modes, i.e., one is the double-support mode, which can manipulate a relatively light object with faster speed, and the other is the quadruple-support mode, which can manipulate a relatively heavy object with lower speed. To control the pivoting gait, a graph model predictive control is applied taking into account of these two gait modes. By adaptively switching the gait mode according to the applied external disturbance, a robot can stably perform the pivoting gait even if the external disturbance is applied to the object.
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