CAREER: A Modular, Embodied Control Strategy for Autonomous Soft Robots

This Faculty Early Career Development (CAREER) award will establish a new strategy for achieving autonomous behaviors in soft robots. Soft robots have been of significant interest in recent years, with their compliance being ideal for sensitive, unstructured, or dynamic applications, e.g., medical robotics, assistive technologies, and manufacturing with fragile components. However, sensing, control, and actuation can be difficult in soft robots, with their soft bodies interfacing poorly with conventional, rigid electronics. Moreover, traditional mechatronic systems are not well-suited for controlling the large number of degrees of freedom of soft materials and may be incompatible with a variety of applications, e.g., in vivo medical applications. In this work, autonomous behaviors such as decisions about trajectory will be embodied in the soft robot itself via stimuli-responsive control modules distributed throughout the robot. The collective action of the control modules in response to the local environment can produce large changes to the shape of the robot’s body and its actuation behavior, and thereby to the gait, trajectory, and function of the robot. This award will also provide training in soft robotics and manufacturing to Pennsylvania high school teachers from rural and urban school districts. The integrated research and teaching plans will include practical strategies for building autonomous soft robots with multimaterial 3D printing and broader engagement of underrepresented and first-generation researchers. The objective of this work is to establish a strategy for embodied sensing and control based on the use of control modules that regulate the shape and/or pneumatic logic of soft robots. The activation and deactivation of the modules will be autonomously regulated by stimuli-responsive materials, such as liquid crystal elastomers and magnetoactive composites, that are integrated with the robot via multimaterial 3D printing. Modules could be moved, added, or removed to reprogram the distributed control system and change the behavior of the robot. This work will use both numerical simulations and experiments with two types of custom soft robots, a kirigami-based robot and a modular rolling robot. The embodied control strategy will be assessed as the robots autonomously navigate through the environment, changing path, and function in response to multiple inputs (e.g., heat and light). This project is supported by the cross-directorate Foundational Research in Robotics program, jointly managed and funded by the Directorates for Engineering (ENG) and Computer and Information Science and Engineering (CISE). This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.