abstract: This thesis introduces the Model-Based Development of Multi-iRobot Toolbox (MBDMIRT), a Simulink-based toolbox designed to provide the means to acquire and practice the Model-Based Development (MBD) skills necessary to design real-time embedded system. The toolbox was developed in the Cyber-Physical System Laboratory at Arizona State University. The MBDMIRT toolbox runs under MATLAB/Simulink to simulate the movements of multiple iRobots and to control, after verification by simulation, multiple physical iRobots accordingly. It adopts the Simulink/Stateflow, which exemplifies an approach to MBD, to program the behaviors of the iRobots. The MBDMIRT toolbox reuses and augments the open-source MATLAB-Based Simulator for the iRobot Create from Cornell University to run the simulation. Regarding the mechanism of iRobot control, the MBDMIRT toolbox applies the MATLAB Toolbox for the iRobot Create (MTIC) from United States Naval Academy to command the physical iRobots. The MBDMIRT toolbox supports a timer in both the simulation and the control, which is based on the local clock of the PC running the toolbox. In addition to the build-in sensors of an iRobot, the toolbox can simulate four user-added sensors, which are overhead localization system (OLS), sonar sensors, a camera, and Light Detection And Ranging (LIDAR). While controlling a physical iRobot, the toolbox supports the StarGazer OLS manufactured by HAGISONIC, Inc. / Dissertation/Thesis / Model-Based Development of Multi-iRobot Toolbox (version 1.0) / M.S. Computer Science 2012

The nodes in wireless sensor networks (WSNs) utilize the radio frequency (RF) channel to communicate. Given that the RF channel is the primary communication channel, many researchers have developed techniques for securing that channel. However, the RF channel is not the only interface into a sensor. The sensing components, which are primarily designed to sense characteristics about the outside world, can also be used (or misused) as a communication (side) channel. In our work, we aim to characterize the side channels for various sensory components (i.e., light sensor, acoustic sensor, and accelerometer). While previous work has focused on the use of these side channels to improve the security and performance of a WSN, we seek to determine if the side channels have enough capacity to potentially be used for malicious activity. Specifically, we evaluate the feasibility and practicality of the side channels using today's sensor technology and illustrate that these channels have enough capacity to enable the transfer of common, well-known malware. Given that a significant number of modern robotic systems depend on the external side channels for navigation and environment-sensing, they become potential targets for side-channel attacks. Therefore, we demonstrate this relatively new form of attack which exploits the uninvestigated but predominantly used side channels to trigger malware residing in real-time robotic systems such as the iRobot Create. The ultimate goal of our work is to show the impact of this new class of attack and also to motivate the need for an intrusion detection system (IDS) that not only monitors the RF channel, but also monitors the values returned by the sensory components.

The Mobile Electronic Dispensary System (MEDS) is an indoor medical dispensary system where robots locate and travel to patients within a grid in order to deliver medication or other medical supplies based on a predefined schedule. For older people or individuals with physical or mental disabilities, it is important to ensure that medications are taken as prescribed. Missing or mixing dosages can cause unwanted and even harmful consequences. As individuals grow older or battle disabilities, it is expected that adhering to their medicine regimen will be a daily challenge without the assistance of a fulltime caregiver. Therefore, to assist individuals in maintaining their independence, MEDS ensures the proper medicine is dispensed to the patient at the prescribed time and dosage. At the core of MEDS is a scheduler that maintains the medicines to be dispensed, including the times and dosages. Once a scheduled time arrives to deliver medicine to a patient, MEDS instructs the appropriate robot to wake up, locate the patient within a defined grid, and then travel to the patient and deliver the medicine. Upon receiving the delivery, the patient will accept the medicine physically and then update their mobile device, informing MEDS that the medicine was successfully delivered. At this time, the robot will return to its home base within the grid. The patients are within the confines of a building where GPS is not a viable solution to track items to pinpoint accuracy. Therefore, an indoor location based system with beacons and listeners are required in order to define a grid and enable robots to locate and travel to the patient. This paper defines and details the programs, database, algorithms, and hardware of MEDS using the Cricket Indoor Location System and iRobot Creates. / text

Aim of this thesis is to search the market for suitable autonomous robot to be used by smart house. The research in this work is partly done on the range of abilities of smart houses in matter of sensor systems, ability of data processing and their use by mobile robots. The output of this thesis is robotics application written using Microsoft Robotics Developer Studio (C#) and simulated using Visual Simulation Environment. Main feature of this robotic application is the interface between robot and smart house, and robot and user. This interface enables employer to directly control robot's movement or to use automated pathfinding. The robot is able to navigate in dynamic environment and to register, interact and eventually forget temporary obstacles.

Aim of this thesis is to search the market for suitable autonomous robot to be used by smart house. The research in this work is partly done on the range of abilities of smart houses in matter of sensor systems, ability of data processing and their use by mobile robots. The output of this thesis is robotics application written using Microsoft Robotics Developer Studio (C#) and simulated using Visual Simulation Environment. Main feature of this robotic application is the interface between robot and smart house, and robot and user. This interface enables employer to directly control robot's movement or to use automated pathfinding. The robot is able to navigate in dynamic environment and to register, interact and eventually forget temporary obstacles.