Engineering Commons^™

Model Based Force Estimation And Stiffness Control For Continuum Robots, Vincent A. Aloi

Doctoral Dissertations

Continuum Robots are bio-inspired structures that mimic the motion of snakes, elephant trunks, octopus tentacles, etc. With good design, these robots can be naturally compliant and miniaturizable, which makes Continuum Robots ideal for traversing narrow complex environments. Their flexible design, however, prevents us from using traditional methods for controlling and estimating loading on rigid link robots.

In the first thrust of this research, we provided a novel stiffness control law that alters the behavior of an end effector during contact. This controller is applicable to any continuum robot where a method for sensing or estimating tip forces and pose exists. …

A Multi-Constraint Predictive Control System With Auxiliary Emergency Controllerfor Autonomous Vehicles, Farhad Partovi Ebrahimpour

Graduate Research Theses & Dissertations

In the last few years, several research groups and companies have worked on developing autonomous vehicles. Among the first automation layers, the safety layer plays a significant role in this field. However, considering safety should not diminish the importance of the efficiency of the vehicle in terms of path tracking with the desired speed. This thesis introduces a multi-constraint predictive control algorithm along with a safety layer to guarantee object avoidance in emergency situations. First, there is a quick review of autonomous cars and their functionalities. In the following, a controller switching mechanism is proposed and designed. It switches the …

Exploration Of Stimulus Current Energy Reduction And Bifurcation Dynamics In Conductance-Based Neuron Models Using Optimal Control Theory, Michael E. Ellinger

Dissertations

Hodgkin-Huxley type conductance-based models can simulate the effect of time-varying injected stimulus currents on the neuron membrane voltage. The dynamics simulated by these model types enables investigation of the biophysical basis of neuronal activity which is fundamental to higher level function. Broadened understanding the basis of nervous system function could lead to development of effective treatment for related diseases, disorders, and the effects of trauma. In this dissertation, optimal control is used with conductance-based neuron models to develop a "Reduced Energy Input Stimulus Discovery Method." Within the method, an objective function balances two competing criteria: tracking a reference membrane voltage …

Caddy: A 2005 Roborodentia Entry With Vision And Path Planning Abilities, Taylor Braun-Jones

Computer Engineering

Roborodentia is an autonomous robotics competition held each year during Cal Poly’s Open House. For the 2005 competition, robot entries needed to navigate a maze searching for three randomly placed golf balls, collect them, and then deposit the balls in the “nest” at the end of the maze. A newly added aspect for the 2005 competition included two bonus balls that were placed on a platform behind the wall in two predetermined corners of the maze.

Caddy is a robot that was entered into the 2005 Roborodentia competition. Caddy included a vision system that allowed searching for balls down untraveled …

Investigation On The Mobile Robot Navigation In An Unknown Environment, Ahmed S. Khusheef

Theses: Doctorates and Masters

Mobile robots could be used to search, find, and relocate objects in many types of manufacturing operations and environments. In this scenario, the target objects might reside with equal probability at any location in the environment and, therefore, the robot must navigate and search the whole area autonomously, and be equipped with specific sensors to detect objects. Novel challenges exist in developing a control system, which helps a mobile robot achieve such tasks, including constructing enhanced systems for navigation, and vision-based object recognition. The latter is important for undertaking the exploration task that requires an optimal object recognition technique.

In …

Architecture For Intelligent Power Systems Management, Optimization, And Storage., J. Chris Foreman

Electronic Theses and Dissertations

The management of power and the optimization of systems generating and using power are critical technologies. A new architecture is developed to advance the current state of the art by providing an intelligent and autonomous solution for power systems management. The architecture is two-layered and implements a decentralized approach by defining software objects, similar to software agents, which provide for local optimization of power devices such as power generating, storage, and load devices. These software device objects also provide an interface to a higher level of optimization. This higher level of optimization implements the second layer in a centralized approach …