Description

While artificial intelligence, robotics and computing power advance at a stunning pace, the physical interactions between such systems remain as an unsolved question. Replacement aftermarket parts for robotics account for $400 billion a year. This figure, comparable to the entire GDP of Belgium, could be reduced if smart materials were combined with robotics and AI to heal robotic parts or prevent damage. The natural healing function has inspired chemists to impart similar properties to synthetic materials, creating “self-healing materials". These materials have the ability to recover their key-properties after damage through a self-healing (SH) mechanism. A broad range of SH materials has been developed, based on a variety of chemical and physical principles, and has led to innovative applications. While Europe was well positioned in the discovery of new SH materials, this project aims to take a leading position in an emerging area of application of these materials. In robotics and machines in general, SH materials and healing abilities have not yet been explored. This project will realize the scientifically ambitious and technologically concrete breakthroughs to exploit the combination of self-healing materials with (damage) sensing capabilities, intelligence and automated healing in soft robotics. This implies the design of anthropomorphic materials, capable of feeling pain. By intelligent control the inflicted damage will prompt the whole system to rest and heal before (more) serious damage occurs, restoring not only structural integrity by reattaching broken parts, but also restoring complex functions like sensing and actuation. To achieve this, dedicated SH materials will be synthesized and characterised, SH actuators and sensors will be created, and dedicated control intelligence for structural health monitoring and autonomous SH procedures will be investigated. All these technologies will be integrated in two demonstrators to disseminate the objectives.
Short titleSHERO
AcronymOZR3414
StatusActive
Effective start/end date1/06/1931/05/22

    Research areas

  • robotics

    Flemish discipline codes

  • Automation, feedback control and robotics

ID: 46609587