This Master’s graduation thesis is a project elaborated for the automotive manufacturer BMW AG. It explores the possibilities given by soft robotic technology to improve comfort while sitting in self-driving vehicles. The project focuses on a specific scenario: a seat that enhances the relaxation experience on the car for long distance travels. An extensive literature research is done on comfort for seat design, soft robotics and BMW strategy on autonomous driving.
Prototypes and material tests are made to understand the possibilities with pneumatic soft actuators, resulting in design directions and requirements.
Concepts are developed by merging soft robotics capabilities together with design opportunities for improve seat’s adaptability. A Machine Learning model is used to train a textile pneumatic actuator to automatically being able to predict its shape via an optical sensing system. This proves the concept’s feasibility. At the end of the thesis, the final concept design, named LightFit, is proposed. The latter is an automated seat with inflatable soft robotic components embedded in its structure that allow the seat to change shape. The ultimate goal of LightFit is to provide long-term comfort by adapting itself to the user’s body contour and by inducing micro-movements that can decrease perceived discomfort over prolonged sitting.