Inverse Dynamics Problems

The inverse dynamics problem was developed in order to provide researchers with the state of the art in inverse problems for dynamic and vibrational systems. Contrasted with a forward problem, which solves for the system output in a straightforward manner, an inverse problem searches for the system input through a procedure contaminated with errors and uncertainties. An inverse problem, with a focus on structural dynamics, determines the changes made to the system and estimates the inputs, including forces and moments, to the system, utilizing measurements of structural vibration responses only. With its complex mathematical structure and need for more reliable input estimations, the inverse problem is still a fundamental subject of research among mathematicians and engineering scientists. This book contains 11 articles that touch upon various aspects of inverse dynamic problems

Autonomous Robot Navigation through a Crowded and Dynamic Environment: Using A Novel form of Path Planning to Demonstrate Consideration towards Pedestrians and other Robots

This thesis presents a novel path planning algorithm for robotic crowd navigation through a pedestrian environment. The robot is designed to negotiate its way through the crowd using considerate movements. Unlike many other path planning algorithms, which assume cooperation with other pedestrians, this algorithm is completely independent and requires only observation. A considerate navigation strategy has been developed in this thesis, which utilises consideration as an directs an autonomous mobile robot. Using simple methods of predicting pedestrian movements, as well as simple relative distance and trajectory measurements between the robot and pedestrians, the robot can navigate through a crowd without causing disruption to pedestrian trajectories. Dynamic pedestrian positions are predicted using uncertainty ellipses. A novel Voronoi diagram-visibility graph hybrid roadmap is implemented so that the path planner can exploit any available gaps in between pedestrians, and plan considerate paths. The aim of the considerate path planner is to have the robot behave in specific ways when moving through the crowd. By predicting pedestrian trajectories, the robot can avoid interfering with them. Following preferences to move behind pedestrians, when cutting across their trajectories; to move in the same direction of the crowd when possible; and to slow down in crowded areas, will prevent any interference to individual pedestrians, as well as preventing an increase in congestion to the crowd as a whole. The effectiveness of the considerate navigation strategy is evaluated using simulated pedestrians, multiple mobile robots loaded with the path planning algorithm, as well as a real-life pedestrian dataset. The algorithm will highlight its ability to move with the aforementioned consideration towards each individual dynamic agent