Cognitive robot control strategies for complex surgical environments
(English) This thesis aims to contribute to the development of robotics autonomy in complex tasks based on the cognitive control paradigm. Cognition is a multidisciplinary approach aimed to provide robotic systems with intelligent and autonomous behaviour that should learn and reason about how to re...
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| Tipo de recurso: | tesis doctoral |
| Estado: | Versión publicada |
| Fecha de publicación: | 2024 |
| País: | España |
| Institución: | CBUC, CESCA |
| Repositorio: | TDR. Tesis Doctorales en Red |
| OAI Identifier: | oai:www.tdx.cat:10803/693379 |
| Acceso en línea: | http://hdl.handle.net/10803/693379 https://dx.doi.org/10.5821/dissertation-2117-424251 |
| Access Level: | acceso abierto |
| Palabra clave: | Àrees temàtiques de la UPC::Enginyeria biomèdica Àrees temàtiques de la UPC::Informàtica 004 617 |
| Sumario: | (English) This thesis aims to contribute to the development of robotics autonomy in complex tasks based on the cognitive control paradigm. Cognition is a multidisciplinary approach aimed to provide robotic systems with intelligent and autonomous behaviour that should learn and reason about how to respond in front of complex tasks and environments.Cognition involves aspects as perception, awareness, interpretation of human actions, learning, planning, anticipating and dynamic response to changes in the working conditions and in the interaction with humans. Autonomy is intended to partially substitute and/or complement the human faculties at the level of perception, analysis and execution. Increasing the level of autonomy of robots allows focusing the humans cognitive load on high level decisions and actions, in aspects where the human factor is essential: contextualisation of information, specific expertise, medical knowledge and complex decision-making among others. Furthermore, robots improve the properties of humans in certain aspects such as precision, repeatability, absence of fatigue or response efficiency in terms of time and accuracy.This thesis addresses different key aspects of robotic autonomy: perception, planning and dynamic execution of actions and, finally, the control structures required for efficient control and their integration in robotic systems.This thesis combines a global theoretical approach supported by practical applications based on the field of robot-assisted minimally invasive surgery. This field has been chosen for two main reasons: the social impact involved in the improvement of surgery and, secondly, because this field of application is highly demanding from both, human and robotic perspective.The experimental phases have focused on various surgical robotic. First, a teleoperated platform with a single robot has been used aimed at minimally invasive fetal surgery in which a cognitive system offers a certain level of autonomy to generate trajectories in collision-free spaces, increasing patient safety and decreasing the cognitive load of surgeons in navigation and interaction tasks within the intra-uterine region. Second, a multi-robot architecture to execute auxiliary actions in a human-robot cooperative system: the main surgeon performs the surgical actions while the auxiliary robots perform, autonomously, auxiliary surgical tasks. With this configuration the experimentation focuses on minimally invasive radical prostatectomy surgery.Thus, the thesis addresses the perception of the anatomical environment, considering the limitations of data acquisition in terms of quality and quantity, as well as the absence of anatomical markers. The next topic that the thesis addresses is the dynamic planning of actions. Different application paradigms have been studied, such as direct human-robot interaction using haptic guidance, movement planning in pseudo-structured environments and, active planning and control in dynamic environments. These proposed environments respond to different surgical scenarios within minimally invasive techniques.Finally, cognitive control applied to robotic platforms is addressed. The followed approach is based on the multi-level decomposition of complex tasks (e.g. surgical procedure) defining all potential states and transitions. This decomposition translates into the use of deterministic and robust control structures that restrict falling into uncontrollable or unexpected situations that put at risk, in the application case, the patient, the surgeons or the auxiliary personnel.Control structures also consider human-robot interaction, robots coordination and cooperation, interaction with the work environment and restrictions imposed by surgery and patient safety.The integration of all these modules: perception, planning and cognitive control, demonstrates the advances achieved in cognitive robotics and their applicability towards a more autonomous robotic surgery. |
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