Networked Vehicle Merging by Cooperative Tracking Control

Cooperative Vehicle Control, Feature Tracking and Ocean Sampling

This dissertation concerns the development of a feedback control framework for coordinating multiple, sensor-equipped, autonomous vehicles into mobile sensing arrays to perform adaptive sampling of observed fields. The use of feedback is central; it maintains the array, i.e. regulates formation position, orientation, and shape, and directs the array to perform its sampling mission in response t...

Nonlinear Robust Tracking Control of an Underwater Vehicle-Manipulator System

This paper develops an improved robust multi-surface sliding mode controller for a complicated five degrees of freedom Underwater Vehicle-Manipulator System with floating base. The proposed method combines the robust controller with some corrective terms to decrease the tracking error in transient and steady state. This approach improves the performance of the nonlinear dynamic control scheme a...

Vehicle Control in Cooperative Driving

Cooperative tracking using mobile robots and environment-embedded, networked sensors

We study the target tracking problem using multiple, environment-embedded, stationary sensors and mobile robots. An architecture for robot motion coordination is presented which exploits a shared topological map of the environment. The stationary sensors and robots maintain region-based density estimates which are used to guide the robots to parts of the environment where unobserved targets may...

Cooperative Tracking with Mobile Robots and Networked Embedded Sensors

We study the target tracking problem using multiple, environment-embedded, stationary sensors and mobile robots. The stationary sensors and robots maintain region-based density estimates which are used to guide the robots to parts of the environment where unobserved targets may be present. Experiments in simulation show that the region-based approach works better than a ‘naive’ target following...