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

No abstract available

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

No abstract available

A system of intelligent algorithms for a module of onboard equipment of mobile vehicles

The area of intelligent robotics is moving from the single robot control problem to that of controlling multiple robots operating together and even collaborating in dynamic and unstructured intelligent environments. In such conditions, an intelligent robot control system is only part of general intelligent system. In this paper, we consider a model of such system. © 2013 Anna Gorbenko

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

Simultaneous Localization and Mapping (SLAM) for Autonomous Driving: Concept and Analysis

The Simultaneous Localization and Mapping (SLAM) technique has achieved astonishing progress over the last few decades and has generated considerable interest in the autonomous driving community. With its conceptual roots in navigation and mapping, SLAM outperforms some traditional positioning and localization techniques since it can support more reliable and robust localization, planning, and controlling to meet some key criteria for autonomous driving. In this study the authors first give an overview of the different SLAM implementation approaches and then discuss the applications of SLAM for autonomous driving with respect to different driving scenarios, vehicle system components and the characteristics of the SLAM approaches. The authors then discuss some challenging issues and current solutions when applying SLAM for autonomous driving. Some quantitative quality analysis means to evaluate the characteristics and performance of SLAM systems and to monitor the risk in SLAM estimation are reviewed. In addition, this study describes a real-world road test to demonstrate a multi-sensor-based modernized SLAM procedure for autonomous driving. The numerical results show that a high-precision 3D point cloud map can be generated by the SLAM procedure with the integration of Lidar and GNSS/INS. Online four–five cm accuracy localization solution can be achieved based on this pre-generated map and online Lidar scan matching with a tightly fused inertial system

Planning and control for microassembly of structures composed of stress-engineered MEMS microrobots

We present control strategies that implement planar microassembly using groups of stress-engineered MEMS microrobots (MicroStressBots) controlled through a single global control signal. The global control signal couples the motion of the devices, causing the system to be highly underactuated. In order for the robots to assemble into arbitrary planar shapes despite the high degree of underactuation, it is desirable that each robot be independently maneuverable (independently controllable). To achieve independent control, we fabricated robots that behave (move) differently from one another in response to the same global control signal. We harnessed this differentiation to develop assembly control strategies, where the assembly goal is a desired geometric shape that can be obtained by connecting the chassis of individual robots. We derived and experimentally tested assembly plans that command some of the robots to make progress toward the goal, while other robots are constrained to remain in small circular trajectories (orbits) until it is their turn to move into the goal shape. Our control strategies were tested on systems of fabricated MicroStressBots. The robots are 240–280 µm × 60 µm × 7–20 µm in size and move simultaneously within a single operating environment. We demonstrated the feasibility of our control scheme by accurately assembling five different types of planar microstructures