Achieving human-like dexterity in robotic hands : inspiration from human hand biomechanics and neuromuscular control

The human hand's unique biomechanical structure and neuromuscular control combine to produce amazing dexterous capabilities in a way that is still not fully understood. The Anatomically Correct Testbed (ACT) hand is a robotic system that is designed as a physical simulation of the human hand, and can help us examine and potentially uncover the roles of biomechanics and neural control in achieving dexterity. In this dissertation, I utilize the ACT hand and other robotic systems to explore the underlying sources of human hand dexterity, with the goal of understanding the fundamental differences between robotic and human hands in terms of (i) mechanical joint/tendon structure and (ii) control strategies. To begin, I develop comprehensive mechanical models that describe the musculoskeletal and tendon mechanics of the fingers and thumb of the human hand. Then, I work to isolate the contributions of biomechanical structure and neuromuscular control toward human dexterity. I have developed and implemented control strategies for achieving fine object manipulation first with the robotic hand of a space humanoid, Robonaut 2, and then with the ACT hand. I examined the unique control challenges, including uncontrollable joints and the requirement of accurate internal models, that arise due to the human hand's complex musculotendon structure and the potential advantages offered by the human hand's design, such as passive joint coupling to facilitate grasp shape adaptation and force production capabilities that are ideally suited for common manipulation tasks. Finally, inspired by the neuromuscular control strategies of the human hand, I have developed a novel hierarchical control strategy for the ACT hand and experimentally demonstrated improved grasp stability and manipulation capabilities compared to conventional robotic control laws. Through an in-depth exploration of human hand biomechanics and neuromuscular control, theoretical control analysis of robotic and human hands, and experimental demonstration of fine object manipulation, this work uncovers crucial insights into the sources of human hand dexterity that have the potential to drive innovative design and control strategies and bring robotic and prosthetic hands closer to human levels of dexterity.Mechanical Engineerin

The Significance of Injuries and Anatomical Patterns of Trauma in Pedestrian and Cyclist Fatalities and their Association with Motor Vehicle Collision Dynamics and Post-Collision Kinematics

Deaths from motor vehicle collisions (MVCs) are a major global health concern, with over 1.35 million fatalities reported annually by the United Nations. More than half involve pedestrians, cyclists, and motorcyclists. Post-mortem examinations by pathologists determine the cause of death and mechanisms of injury and play a significant role in the investigation of the deaths of vulnerable road users. The purpose of this study was to understand the injury patterns sustained by pedestrians and cyclists fatally injured in motor vehicle impacts. This study reviews the development of injury patterns described in the medical literature and identifies their limitations in the context of the current motor vehicle fleet, which includes various types of vehicles such as vans, sports utility, and pickup trucks. The main objectives of this research were to determine injury patterns in pedestrians and cyclists killed in MVCs and compare them with the historical or “classical triads”. The study also aimed to investigate factors related to pedestrian and cyclist kinematics, MVC dynamics, and vehicle type, maneuver, and speed on injury patterns. Multivariate logistic regression models were developed to identify variables that were associated with specific serious to maximal injuries. Data from 766 post-mortems done between 2013 and 2019 in Ontario were collected. There were 670 pedestrian fatalities and 96 cyclist fatalities. Distinct injury patterns emerged based on age groups, kinematics, vehicle type, vehicle maneuver, and speed. The findings highlighted variations in injury patterns between children, youth, adults, and the elderly, emphasizing the importance of considering age-specific factors when studying trauma. Based on the multivariate logistic regression models, recommendations have been made to assist pathologists, coroners, and police collision reconstructionists in their analysis of fatal pedestrian and cyclist-MVCs. Overall, this research contributes to a better understanding of the specific fatal injury patterns sustained by pedestrians and cyclists involved in MVCs. By considering collision dynamics, vehicle type, and other relevant factors, this study provides valuable insights for assisting MVC reconstruction and investigation, and postmortem assessment supporting future motor vehicle research and regulation in mitigating and preventing serious injuries