Design Optimization

• Motivation: improve the robotic bat B2’s design by matching it to actual biological bats
• Used Principal Component Analysis (PCA) to extract dominant modes of flight from kinematics data of bats flying in a wind tunnel
• Developed a parametric kinematic model of the wings and a constrained nonlinear optimization to optimize wing parameters and actuator trajectories
• Resulted in improved matching of B2’s kinematics to biology

J. Hoff, A. Ramezani, S.-J. Chung, S. Hutchinson, “Synergistic design of a bio-inspired micro aerial vehicle with articulated wings,” in Robotics: Science and Systems, 2016.

• Motivation: synchronize flapping and folding for robotic bat flight with a single actuator
• Designed a mechanism that couples flapping and folding using a rigid mechanism
• Applied the previous optimization methods to modify the kinematic parameters and actuator trajectories to best mimic the biological data
• New system matches biological kinematic data in spite of reducing the number of actuators

J. Hoff, A. Ramezani, S.-J. Chung, S. Hutchinson, “Reducing versatile bat wing conformations to a 1-DoF machine,” in Living Machines, 2017.

• Motivation: improve lift generation of B2 while mimicking the kinematics of biological bats
• Used the methods from RSS 2016 and the coupling mechanism from Living Machines 2017 to couple folding and flapping and optimize the structure to match biology
• Demonstrated lift improvements of the flapping system when using this new design

J. Hoff, A. Ramezani, S.-J. Chung, S. Hutchinson, “Optimizing the structure and movement of a robotic bat with biological kinematic synergies,” The International Journal of Robotics Research, vol. 37, no. 10, 2018.