Optimizing the structure and movement of a robotic bat with biological kinematic synergies

In this article, we present methods to optimize the design and flight characteristics of a biologically inspired bat-like robot. In previous, work we have designed the topological structure for the wing kinematics of this robot; here we present methods to optimize the geometry of this structure, and to compute actuator trajectories such that its wingbeat pattern closely matches biological counterparts. Our approach is motivated by recent studies on biological bat flight that have shown that the salient aspects of wing motion can be accurately represented in a low-dimensional space. Although bats have over 40 degrees of freedom (DoFs), our robot possesses several biologically meaningful morphing specializations. We use principal component analysis (PCA) to characterize the two most dominant modes of biological bat flight kinematics, and we optimize our robot’s parametric kinematics to mimic these. The method yields a robot that is reduced from five degrees of actuation (DoAs) to just three, and that actively folds its wings within a wingbeat period. As a result of mimicking synergies, the robot produces an average net lift improvesment of 89% over the same robot when its wings cannot fold

Optimizing the structure and movement of a robotic bat with biological kinematic synergies

In this article, we present methods to optimize the design and flight characteristics of a biologically inspired bat-like robot. In previous, work we have designed the topological structure for the wing kinematics of this robot; here we present methods to optimize the geometry of this structure, and to compute actuator trajectories such that its wingbeat pattern closely matches biological counterparts. Our approach is motivated by recent studies on biological bat flight that have shown that the salient aspects of wing motion can be accurately represented in a low-dimensional space. Although bats have over 40 degrees of freedom (DoFs), our robot possesses several biologically meaningful morphing specializations. We use principal component analysis (PCA) to characterize the two most dominant modes of biological bat flight kinematics, and we optimize our robot’s parametric kinematics to mimic these. The method yields a robot that is reduced from five degrees of actuation (DoAs) to just three, and that actively folds its wings within a wingbeat period. As a result of mimicking synergies, the robot produces an average net lift improvesment of 89% over the same robot when its wings cannot fold

Optimizing the structure and movement of a robotic bat with biological kinematic synergies

In this thesis we present methods to optimize the design and flight characteristics of a biologically-inspired bat-like robot. Recent work has designed the topological structure for the wing kinematics of this robot; here we present methods to optimize the geometry of this structure, and to compute actuator trajectories that yield successful flight behaviors. Our approach is motivated by recent studies on biological bat flight, which have shown that the salient aspects of wing motion can be accurately represented in a low-dimensional space. We use principal components analysis (PCA) to characterize the dominant modes of biological bat flight kinematics, and optimize our robotic design to mimic these. In particular, we use the first and second principal components to shape the parametric kinematics and actuator trajectories through finite state nonlinear constrained optimization. The method yields a robot mechanism that, despite having only five degrees of actuation, possesses several biologically meaningful morphing specializations. We have validated our approach in both simulation and flight experiments with our prototype robotic bat