Towards achieving power autonomy in soft-actuated micro aerial robots

Micro aerial robots with insect-like flight capabilities hold immense promise for various applications, including environmental monitoring, precision agriculture, and infrastructure inspection in confined spaces. However, realizing power autonomy in these miniature robotic platforms presents significant challenges due to weight constraints, power density limitations, and inefficient actuation at small scales. This dissertation presents three essential improvements towards achieving power autonomy in soft-actuated micro aerial robots. Our robotic platform is driven by a dielectric elastomer actuator (DEA) and generates lift force through flapping wings, a similar mechanism found in flying insects. First, we implemented a dynamic model to optimize the robot components for pairing with an improved DEA to generate a higher lift force. The robot achieved a peak lift-to-weight ratio of 4.3 and demonstrated a 20-second hovering flight with position and attitude errors smaller than 2.5 cm and 2◦ . Second, we fabricated a lightweight high-voltage boost converter that transformed a 7 V DC input into an AC waveform of 600 V and 400 Hz to drive the actuator. This is the first onboard boost converter that can drive the soft-actuated micro aerial robot to take off, and it represents a substantial achievement in miniaturizing power electronics for microrobots. Third, we took inspiration from the natural autorotation of maple seeds in their slow descent. We implemented the first samara-inspired mechanism on micro aerial robots, enhancing lift generation while maintaining in-flight attitude stability without feedback control. The 1.22-gram vehicle can stably take off in 1 second with a total input thrust of 1 gram-force. These accomplishments provide a pathway towards achieving power autonomy and open opportunities for developing agile, robust, and autonomous micro aerial robots for diverse applications.

Name thesis:degree_name

Doctoral

Department dc:contributor.department

Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science

Grantor dc:publisher

Massachusetts Institute of Technology

Year dc:date.issued

2025

Author dc:creator

• Ren, Zhijian

Advisor dc:contributor.advisor

• Chen, Yufeng (Kevin)

Statement dc:rights

• In Copyright - Educational Use Permitted
• Copyright retained by author(s)

Licence dc:rights.uri

• https://rightsstatements.org/page/InC-EDU/1.0/

Handle dc:identifier.uri

https://hdl.handle.net/1721.1/164161

OAI identifier oai:identifier

oai:dspace.mit.edu:1721.1/164161