Abstract
This study proposes to develop, build and implement the IoT of the mobile network robot integrated with features of mapping and location in an internal environment, to trace the best route and obtain a fast and efficient change to detect changes in the environment as an identifier of falls in the elderly. It is observed that it is applied research to aggregate several available algorithms. The robot was provided with internal mapping and location capabilities to map the best route and achieve fast and active movements in a retirement home for the elderly. The mobile robot was also set up to monitor and assist in the transport of medicines and notify the caregiver of any incident with the elderly within its environment. A mobile app controls system and robot development. The main phases are highlighted: definition and acquisition of the model and the components used (mechanical structure, microcontroller, sensors and actuators); application development of user-system interaction; development and construction of a robot, auxiliary modules (environment) and central module; and integration experiments. Monitoring and mapping of the environment are performed using Wall-Following, Simultaneous Location and Mapping (SLAM) and Sensor Fusion techniques. The precise movements of the robot are assured through a combination of navigation and control techniques. Moreover, the robot received internal mapping and location, resources to map the best route and obtain quick and active movements in Institutions of Long Stay for the Elderly (L.T.C.F.). Besides, the performance of the following algorithms was analyzed and compared: Breadth-First Search (B.F.S.), Depth First Search (D.F.S.), and Wall-Following. The B.F.S. algorithm obtained the best results for the minimum path.
Highlights
Knowledge of the environment without human interference is one of the essential skills of an autonomous robot
Identification of the location based on the previous estimate is incremental, that is, measurement errors are accumulated along the route and this orientation capacity in the environment inserted is limited to land, wheeled or crawler mobile robots
TOPICS RELATED TO MOBILE ROBOTICS AND THE INTERNET OF THINGS The main topics needed to understand the proposal developed by integrating the IoT and mobile robotics applied to internal monitoring are listed and explained below
Summary
Knowledge of the environment without human interference is one of the essential skills of an autonomous robot. Identification of the location based on the previous estimate is incremental, that is, measurement errors are accumulated along the route and this orientation capacity in the environment inserted is limited to land, wheeled or crawler mobile robots. To reduce such biases, some strategies are used, such as Inertial Measurement Units (IMUs), Global Positioning System (G.P.S.) and LASER Odometry [13], [18]. New research proposes to develop, build and implement the integrated network mobile robot IoT with mapping and location capabilities in an indoor environment, in order to trace the best route and get a fast and efficient shifting to detect changes in the environment.
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