Open Access. Powered by Scholars. Published by Universities.®
- Keyword
-
- Automated Driving (1)
- Autonomous Vehicles (1)
- Autonomous driving (1)
- CDPR (1)
- Decision Process (1)
-
- Deep Reinforcement Learning (1)
- Density (1)
- Formal methods (1)
- Game Theory (1)
- Human-robot interaction (1)
- Human-robot interaction (HRI) (1)
- Inverse reinforcement learning (1)
- Model checking (1)
- Monte Carlo Tree Search (1)
- Motion planning (1)
- Multi-robot system (1)
- Multiple Model Adaptive Estimation (MMAE) (1)
- Navigation (1)
- Operator Theory (1)
- Quadruped (1)
- RCDPR (1)
- Reciprocal Screw Theory (1)
- Reconfigurable Cable Driven Parallel Robots (1)
- Redundancy Resolution Control (1)
- Trust model (1)
- Vehicle-to-vehicle (V2V) communication (1)
- Publication
Articles 1 - 6 of 6
Full-Text Articles in Controls and Control Theory
Controlled Manipulation And Transport By Microswimmers In Stokes Flows, Jake Buzhardt
Controlled Manipulation And Transport By Microswimmers In Stokes Flows, Jake Buzhardt
All Dissertations
Remotely actuated microscale swimming robots have the potential to revolutionize many aspects of biomedicine. However, for the longterm goals of this field of research to be achievable, it is necessary to develop modelling, simulation, and control strategies which effectively and efficiently account for not only the motion of individual swimmers, but also the complex interactions of such swimmers with their environment including other nearby swimmers, boundaries, other cargo and passive particles, and the fluid medium itself. The aim of this thesis is to study these problems in simulation from the perspective of controls and dynamical systems, with a particular focus …
Safe Navigation Of Quadruped Robots Using Density Functions, Andrew Zheng
Safe Navigation Of Quadruped Robots Using Density Functions, Andrew Zheng
All Theses
Safe navigation of mission-critical systems is of utmost importance in many modern autonomous applications. Over the past decades, the approach to the problem has consisted of using probabilistic methods, such as sample-based planners, to generate feasible, safe solutions to the navigation problem. However, these methods use iterative safety checks to guarantee the safety of the system, which can become quite complex. The navigation problem can also be solved in feedback form using potential field methods. Navigation function, a class of potential field methods, is an analytical control design to give almost everywhere convergence properties, but under certain topological constraints and …
Deep Reinforcement Learning And Game Theoretic Monte Carlo Decision Process For Safe And Efficient Lane Change Maneuver And Speed Management, Shahab Karimi
All Dissertations
Predicting the states of the surrounding traffic is one of the major problems in automated driving. Maneuvers such as lane change, merge, and exit management could pose challenges in the absence of intervehicular communication and can benefit from driver behavior prediction. Predicting the motion of surrounding vehicles and trajectory planning need to be computationally efficient for real-time implementation. This dissertation presents a decision process model for real-time automated lane change and speed management in highway and urban traffic. In lane change and merge maneuvers, it is important to know how neighboring vehicles will act in the imminent future. Human driver …
Modeling, Control And Estimation Of Reconfigurable Cable Driven Parallel Robots, Adhiti Raman Thothathri
Modeling, Control And Estimation Of Reconfigurable Cable Driven Parallel Robots, Adhiti Raman Thothathri
All Dissertations
The motivation for this thesis was to develop a cable-driven parallel robot (CDPR) as part of a two-part robotic device for concrete 3D printing. This research addresses specific research questions in this domain, chiefly, to present advantages offered by the addition of kinematic redundancies to CDPRs. Due to the natural actuation redundancy present in a fully constrained CDPR, the addition of internal mobility offers complex challenges in modeling and control that are not often encountered in literature.
This work presents a systematic analysis of modeling such kinematic redundancies through the application of reciprocal screw theory (RST) and Lie algebra while …
Multi-Robot Symbolic Task And Motion Planning Leveraging Human Trust Models: Theory And Applications, Huanfei Zheng
Multi-Robot Symbolic Task And Motion Planning Leveraging Human Trust Models: Theory And Applications, Huanfei Zheng
All Dissertations
Multi-robot systems (MRS) can accomplish more complex tasks with two or more robots and have produced a broad set of applications. The presence of a human operator in an MRS can guarantee the safety of the task performing, but the human operators can be subject to heavier stress and cognitive workload in collaboration with the MRS than the single robot. It is significant for the MRS to have the provable correct task and motion planning solution for a complex task. That can reduce the human workload during supervising the task and improve the reliability of human-MRS collaboration. This dissertation relies …
Control, Decision-Making, And Learning Approaches For Connected And Autonomous Driving Systems With Humans-In-The-Loop, Fangjian Li
All Dissertations
By virtue of vehicular connectivity and automation, the vehicle becomes increasingly intelligent and self-driving capable. However, no matter what automation level the vehicle can achieve, humans will still be in the loop despite their roles. First, considering the manual driving car as a disturbance to the connected and autonomous vehicles (CAVs), a novel string stability is proposed for mixed traffic platoons consisting of both autonomous and manual driving cars to guarantee acceptable motion fluctuation and platoon safety. Furthermore, humans are naturally considered as the rider in the passenger vehicle. A human-centered cooperative adaptive cruise control (CACC) is designed to improve …