Subventions et des contributions :

Subvention ou bourse octroyée s'appliquant à plus d'un exercice financier. (2017-2018 à 2022-2023)

Conventional robotic manipulators with finite-number of serially-connected rigid links have not been successful in tackling complex tasks in unstructured and confined environments. Examples include many minimally-invasive surgery applications, search and rescue operations in confined environments, and various maintenance operations in nuclear and aerospace industries. Alternatively, continuum robots (CRs) have been proposed that, due to their “continuous backbone structures,” present a “compliant” interface to the environment. Thus CRs offer a number of advantages over traditional manipulators, such as lower cost, safe maneuverability in confined environments, and adaptability to variations in environmental contact conditions. Therefore, CRs are expected to have a significant impact on the cost and applicability of robots in various domains. However, research on autonomous CRs is fairly new and many issues remain to be addressed to overcome their shortcomings, such as low stiffness, small payload, low accuracy, poor manipulability, and often limited workspace and dexterity.

We have recently proposed the new concept of cooperative CRs (CCRs) to not only overcome the aforementioned limitations of CRs but also assimilate reconfigurability for enhancing their adaptation capability to new tasks. However, many theoretical and practical aspects of autonomous CCRs are remaining largely untreated. With a focus on image-based techniques for CCRs, we expect to make significant advancements in the foundations of CCRs by merging our on-going synergetic research on (i) vision-based control of robots, and (ii) CR modeling and control. The objectives of this program include the development and validation of: (1) advanced kineto-static models; (2) novel methods for real-time image-based shape and force sensing; (3) robust and generic visual-servo control techniques; (4) the first robust and active non-rigid structure-from-motion frameworks; and (5) the use of the control results in robot-assisted interventions for medical and security-defence applications.

The proposed multidisciplinary research program is anticipated to produce the first kinematic modeling, sensing, and control techniques for CCRs, enabling many important capabilities, such as enhanced efficiency and accuracy of navigation, improved dexterity and stiffness, and increased robustness of operation in unstructured and dynamic environments. These techniques will open up a host of new robot applications design opportunities, supporting Canadian industries in aerospace, defence, service, manufacturing, energy, and healthcare systems. Furthermore, this research will lead to new research directions and benefit overlapping research areas in robotics, control, computer vision, biomedical engineering, and autonomous systems.