Sensor System for Rescue Robots

A majority of rescue worker fatalities are a result of on-scene responses. Existing technologies help assist the first responders in scenarios of no light, and there even exist robots that can navigate radioactive areas. However, none are able to be both quickly deployable and enter hard to reach or unsafe areas in an emergency event such as an earthquake or storm that damages a structure. In this project we created a sensor platform system to augment existing robotic solutions so that rescue workers can search for people in danger while avoiding preventable injury or death and saving time and resources. Our results showed that we were able to map out a 2D map of the room with updates for robot motion on a display while also showing a live thermal image in front of the system. The system is also capable of taking a digital picture from a triggering event and then displaying it on the computer screen. We discovered that data transfer plays a huge role in making different programs like Arduino and Processing interact with each other. Consequently, this needs to be accounted for when improving our project. In particular our project is wired right now but should deliver data wirelessly to be of any practical use. Furthermore, we dipped our feet into SLAM technologies and if our project were to become autonomous, more research into the algorithms would make this autonomy feasible

Collective cluster-based map merging in multi robot SLAM

New challenges arise with multi-robotics, while information integration is among the most important problems need to be solved in this field. For mobile robots, information integration usually refers to map merging . Map merging is the process of combining partial maps constructed by individual robots in order to build a global map of the environment. Different approaches have been made toward solving map merging problem. Our method is based on transformational approach, in which the idea is to find regions of overlap between local maps and fuse them together using a set of transformations and similarity heuristic algorithms. The contribution of this work is an improvement made in the search space of candidate transformations. This was achieved by enforcing pair-wise partial localization technique over the local maps prior to any attempt to transform them. The experimental results show a noticeable improvement (15-20%) made in the overall mapping time using our technique

Autonomous Vehicle Control

A practical knowledge base in the emerging field of Robotics was developed and used to create a framework for further experiments. The framework was designed such that modular parts could be replaced, allowing for future development without reinventing the wheel . To prove the framework, a semi-autonomous robot was implemented, including stereo vision sensors, an inertial navigation system, and a simultaneous localization and mapping algorithm

Computational intelligence approaches to robotics, automation, and control [Volume guest editors]

No abstract available

Viewfinder: final activity report

The VIEW-FINDER project (2006-2009) is an 'Advanced Robotics' project that seeks to apply a semi-autonomous robotic system to inspect ground safety in the event of a fire. Its primary aim is to gather data (visual and chemical) in order to assist rescue personnel. A base station combines the gathered information with information retrieved from off-site sources. The project addresses key issues related to map building and reconstruction, interfacing local command information with external sources, human-robot interfaces and semi-autonomous robot navigation. The VIEW-FINDER system is a semi-autonomous; the individual robot-sensors operate autonomously within the limits of the task assigned to them, that is, they will autonomously navigate through and inspect an area. Human operators monitor their operations and send high level task requests as well as low level commands through the interface to any nodes in the entire system. The human interface has to ensure the human supervisor and human interveners are provided a reduced but good and relevant overview of the ground and the robots and human rescue workers therein

Design and Implementation of Indoor Disinfection Robot System

After the outbreak of COVID-19 virus, disinfection has become one of the important means of epidemic prevention. Traditional manual disinfection can easily cause cross infection problems. Using robots to complete disinfection work can reduce people's social contact and block the spread of viruses. This thesis implements an engineering prototype of a indoor disinfection robot from the perspective of product development, with the amin of using robots to replace manual disinfection operations. The thesis uses disinfection module, control module and navigation module to compose the hardware of the robot. The disinfection module uses ultrasonic atomizers, UV-C ultraviolet disinfection lamps, and air purifiers to disinfect and disinfect the ground and air respectively. The control module is responsible for the movement and obstacle avoidance of the robot. The navigation module uses Raspberry Pi and LiDAR to achieve real-time robot positioning and two-dimensional plane mapping. In terms of robot software,we have done the following work: (1) Based on the ROS framework, we have implemented functions such as SLAM mapping, location positioning, and odometer data calibration.(2) Customize communication protocols to manage peripheral devices such as UV-C lights, ultrasonic atomizers, air purifiers, and motors on the control board. (3) Develop an Android mobile app that utilizes ROSBridge's lightweight communication architecture to achieve cross platform data exchange between mobile devices and navigation boards, as well as network connectivity and interaction between mobile phones and robots Finally, this thesis implements an engineering prototype of a household disinfection robot from the perspective of product development