Bioinspired robotic rehabilitation tool for lower limb motor learning after stroke

Mención Internacional en el título de doctorEsta tesis doctoral presenta, tras repasar la marcha humana, las principales patologíıas y condiciones que la afectan, y los distintos enfoques de rehabilitación con la correspondiente implicación neurofisiológica, el camino de investigación que desemboca en la herramienta robótica de rehabilitación y las terapias que se han desarrollado en el marco de los proyectos europeos BioMot: Smart Wearable Robots with Bioinspired Sensory-Motor Skills y HANK: European advanced exoskeleton for rehabilitation of Acquired Brain Damage (ABD) and/or spinal cord injury’s patients, y probado bajo el paraguas del proyecto europeo ASTONISH: Advancing Smart Optical Imaging and Sensing for Health y el proyecto nacional ASSOCIATE: A comprehensive and wearable robotics based approach to the rehabilitation and assistance to people with stroke and spinal cord injury.This doctoral thesis presents, after reviewing human gait, the main pathologies and conditions that affect it, and the different rehabilitation approaches with the corresponding neurophysiological implications, the research journey that leads to the development of the rehabilitation robotic tool, and the therapies that have been designed, within the framework of the European projects BioMot: Smart Wearable Robots with Bioinspired Sensory-Motor Skills and HANK: European advanced exoskeleton for rehabilitation of Acquired Brain Damage (ABD) and/or spinal cord injury’s patients and tested under the umbrella of the European project ASTONISH: Advancing Smart Optical Imaging and Sensing for Health and the national project ASSOCIATE: A comprehensive and wearable robotics based approach to the rehabilitation and assistance to people with stroke and spinal cord injury.This work has been carried out at the Neural Rehabilitation Group (NRG), Cajal Institute, Spanish National Research Council (CSIC). The research presented in this thesis has been funded by the Commission of the European Union under the BioMot project - Smart Wearable Robots with Bioinspired Sensory-Motor Skills (Grant Agreement number IFP7-ICT - 611695); under HANK Project - European advanced exoskeleton for rehabilitation of Acquired Brain Damage (ABD) and/or spinal cord injury’s patients (Grant Agreements number H2020-EU.2. - PRIORITY ’Industrial leadership’ and H2020-EU.3. - PRIORITY ’Societal challenges’ - 699796); also under the ASTONISH Project - Advancing Smart Optical Imaging and Sensing for Health (Grant Agreement number H2020-EU.2.1.1.7. - ECSEL - 692470); with financial support of Spanish Ministry of Economy and Competitiveness (MINECO) under the ASSOCIATE project - A comprehensive and wearable robotics based approach to the rehabilitation and assistance to people with stroke and spinal cord injury (Grant Agreement number 799158449-58449-45-514); and with grant RYC-2014-16613, also by Spanish Ministry of Economy and Competitiveness.Programa de Doctorado en Ingeniería Eléctrica, Electrónica y Automática por la Universidad Carlos III de MadridPresidente: Fernando Javier Brunetti Fernández.- Secretario: Dorin Sabin Copaci.- Vocal: Antonio Olivier

Adaptive robust interaction control for low-cost robotic grasping

Robotic grasping is a challenging area in the field of robotics. When a gripper starts interacting with an object to perform a grasp, the mechanical properties of the object (stiffness and damping) will play an important role. A gripper which is stable in isolated conditions, can become unstable when coupled to an object. This can lead to the extreme condition where the gripper becomes unstable and generates excessive or insufficient grip force resulting in the grasped object either being crushed, or falling and breaking. In addition to the stability issue, grasp maintenance is one of the most important requirements of any grasp where it guarantees a secure grasp in the presence of any unknown disturbance. The term grasp maintenance refers to the reaction of the controller in the presence of external disturbances, trying to prevent any undesired slippage. To do so, the controller continuously adjusts the grip force. This is a challenging task as it requires an accurate model of the friction and object’s weight to estimate a sufficient grip force to stop the object from slipping while incurring minimum deformation. Unfortunately, in reality, there is no solution which is able to obtain the mechanical properties, frictional coefficient and weight of an object before establishing a mechanical interaction with it. External disturbance forces are also stochastic meaning they are impossible to predict. This thesis addresses both of the problems mentioned above by:Creating a novel variable stiffness gripper, capable of grasping unknown objects, mainly those found in agricultural or food manufacturing companies. In addition to the stabilisation effect of the introduced variable stiffness mechanism, a novel force control algorithm has been designed that passively controls the grip force in variable stiffness grippers. Due to the passive nature of the suggested controller, it completely eliminates the necessity for any force sensor. The combination of both the proposed variable stiffness gripper and the passivity based control provides a unique solution for the stable grasp and force control problem in tendon driven, angular grippers.Introducing a novel active multi input-multi output slip prevention algorithm. The algorithm developed provides a robust control solution to endow direct drive parallel jaw grippers with the capability to stop held objects from slipping while incurring minimum deformation; this can be done without any prior knowledge of the object’s friction and weight. The large number of experiments provided in this thesis demonstrate the robustness of the proposed controller when controlling parallel jaw grippers in order to quickly grip, lift and place a broad range of objects firmly without dropping or crushing them. This is particularly useful for teleoperation and nuclear decommissioning tasks where there is often no accurate information available about the objects to be handled. This can mean that pre-programming of the gripper is required for each different object and for high numbers of objects this is impractical and overly time-consuming. A robust controller, which is able to compensate for any uncertainties regarding the object model and any unknown external disturbances during grasping, is implemented. This work has advanced the state of the art in the following two main areas: Direct impedance modulation for stable grasping in tendon driven, angular grippers. Active MIMO slip prevention grasp control for direct drive parallel jaw grippers

Bio-Inspired Robotics

Modern robotic technologies have enabled robots to operate in a variety of unstructured and dynamically-changing environments, in addition to traditional structured environments. Robots have, thus, become an important element in our everyday lives. One key approach to develop such intelligent and autonomous robots is to draw inspiration from biological systems. Biological structure, mechanisms, and underlying principles have the potential to provide new ideas to support the improvement of conventional robotic designs and control. Such biological principles usually originate from animal or even plant models, for robots, which can sense, think, walk, swim, crawl, jump or even fly. Thus, it is believed that these bio-inspired methods are becoming increasingly important in the face of complex applications. Bio-inspired robotics is leading to the study of innovative structures and computing with sensory–motor coordination and learning to achieve intelligence, flexibility, stability, and adaptation for emergent robotic applications, such as manipulation, learning, and control. This Special Issue invites original papers of innovative ideas and concepts, new discoveries and improvements, and novel applications and business models relevant to the selected topics of ``Bio-Inspired Robotics''. Bio-Inspired Robotics is a broad topic and an ongoing expanding field. This Special Issue collates 30 papers that address some of the important challenges and opportunities in this broad and expanding field

Proceedings of the 2018 Canadian Society for Mechanical Engineering (CSME) International Congress

Published proceedings of the 2018 Canadian Society for Mechanical Engineering (CSME) International Congress, hosted by York University, 27-30 May 2018

Task Allocation in Foraging Robot Swarms:The Role of Information Sharing

Autonomous task allocation is a desirable feature of robot swarms that collect and deliver items in scenarios where congestion, caused by accumulated items or robots, can temporarily interfere with swarm behaviour. In such settings, self-regulation of workforce can prevent unnecessary energy consumption. We explore two types of self-regulation: non-social, where robots become idle upon experiencing congestion, and social, where robots broadcast information about congestion to their team mates in order to socially inhibit foraging. We show that while both types of self-regulation can lead to improved energy efficiency and increase the amount of resource collected, the speed with which information about congestion flows through a swarm affects the scalability of these algorithms