The paper develops an auto mobile robotics that has the feature of image identification through a set of designed experiments. It is used in automatic industry and the application of AGV. The main controller of mobile robot is myRIO-1900 which is developed by America National Instruments. The inner controller is ARM Cortex-A9, it has two I/O ports, and it adopts MXP and MSP. This device includes and integrates analogy input, analogy output, digital I/O, LED, a button, accelerator, a set of Xilinx FPGA, processor, memory, hard disk, and image identification processing module. It uses Tetrix and Matrix components combining with RC motor to be an arm to solve Competition problem, and it also uses trapezoidal acceleration algorithm and PID algorithm to control more precisely. It applies NI LabVIEW Vision Assistant to do image identification processing to help mobile robot finish specified action.

This paper focuses on implementation of path planning and control for Avrora Unior robot car that enable autonomous parallel parking. Path planning is based on existing geometrical approach, which was modified to fit specific kinematics of the robot shape and control geometry. Geometry and parking space size determine path key points: steering and counter-steering points. We implemented and tested the algorithm using Avrora Unior robot model in Gazebo simulator.

The application of Internet of Things (IoT) has been widely used in our lives with the advancement of related software and hardware technologies. In order to make these IoT modules more intelligent, many IoT modules have begun to incorporate artificial intelligence algorithms. Therefore, this paper develops IoT module with STM32 chip as main controller. This module uses fuzzy analytic hierarchy process (fuzzy-AHP) and adaptive fusion method (AFM) to improve the correctness and self-learning ability of the sensor. In terms of communication, the IoT module has Ethernet, Wi-Fi, LoRa, etc. communication interfaces. We also built a web server on this module, so the IoT module can operate directly in the browser. Finally, we developed a monitoring system. Through this monitoring system, multiple IoT modules can be constructed into a sensor network. This monitoring system can also use same algorithm to correct and isolate data from modules or sensors in the network to make this module more intelligent and applicable in different areas.

Automated guided vehicle is the most important research issues for mobile robot development. The important research issue of the automated guided vehicle (AGV) is navigation system in recent years. Navigation system can be divided into self-localization, path planning and obstacle avoidance for ind oor service execution. The application fields have security patrol or package delivery. Furthermore, recharging is necessary before the battery power has exhausted. The paper develops the automated guided vehicle that is designed and built with a 4WD mecanum wheel platform. Due to the laser ranger's high precision, we applied the laser range finder to achieve the environment map construction, so the self-localization via particles filter (PF) and the path planning algorithms can be utilized with the map. The practical motion and safety avoidance strategies are also proposed for robot motion control. Finally, the sensory fusion methods are also integrated with the laser ranger and RGB-D camera for automated guided vehicle while performing the docking process. The experimental results show the successful demonstrations of autonomous patrol and docking for self-recharging.

Recent developments in 3D reconstruction systems enable to capture an environment in great detail. Several studies have provided algorithms that deal with a path-planning problem of total coverage of observable space in time-efficient manner. However, not much work was done in the area of globally optimal solutions in dense clutter environments. This paper presents a novel solution for autonomous exploration of a cluttered 2.5D environment using an unmanned ground mobile vehicle, where robot locomotion is limited to a 2D plane, while obstacles have a 3D shape. Our exploration algorithm increases coverage of 3D environment mapping comparatively to other currently available algorithms. The algorithm was implemented and tested in randomly generated dense clutter environments in MATLAB.

In this work, a mobile robot is equipped with an industrial barcode scanner which can provide the pose information respect to the barcode tag in the field of view (FOV). For real multiple automated guided vehicle (AGV) transportation applications, the mobile robot navigation flow is considered to get the global checkerboard type path planning from a remote master server as an input. For the local planner, each robot is applied with a simple path controller to track the global path. The simulation and experimental results show that this implementation has good feasibility for multi robot co-working in a factory area.

Gas detection is very cumbersome because the gas will diffuse and mix with other gases. A handheld gas detector with IoT function using a single-chip controller will be developed in this paper. This detector consists of a variety of different gas sensors. Adaptive fusion method is used to integrate sensing information from different sensors to improve the correctness and gas identification of this detector. Since this gas detection module is hand-held, we use wireless communication interfaces such as Wi-Fi and LoRa with bands at 433/868/915 MHz to enable this gas detector to be able to transmit data while moving. In addition, multiple gas detection modules can be used to form a detection network for large area detection. A built-in algorithm can assist in the correction and isolation of data from modules or sensors in the detection network. Therefore, the gas detecting module can be more flexible in use.

The paper develops the MyRio based mobile platform with a robot arm. The structure of the mobile platform uses the Matrix elements. The Matrix elements build the robot arm with four degrees of freedoms, too. The mobile platform integrates some sensors, four DC servomotors, two DC motors, two RC servomotors, a MyRio based control box, and two vision devices. The core controller of the MyRio-1900 control box is the NI-Single-Board RIO 9606 module. The mobile platform embeds a robot arm on the frond side. The driver device of the gripper is a RC servomotor. The developed mobile platform uses ultrasonic sensors to detect the obstacles. Trapezoidal acceleration and deceleration algorithm and Proportional-Integral-Derivative (PID) algorithm are used for precise motion control of each DC servomotor. A vision device of the mobile platform can search and recognize the shape and color of the assigned billiard ball. The other recognizes the symbol of each QR code. These vision devices are fixed on the frond side of the mobile platform, and recognize the assigned object using Otsu algorithm. In the experimental results, the mobile platform tests the positioning function of the Proportional-Integral-Derivative (PID) algorithm for each DC servomotor. Then we implement the movement precious of the mobile platform.

Autonomous exploration and coverage in 3D environments recently has became a rapidly developing research field. Emerging 3D reconstruction methods, designed specifically for exploration and coverage, allows capturing an environment in a greater details. However, not much work addresses certain difficulties inherent to dense clutter environments. We observed those difficulties and made an attempt that seeks to expand the applicability of such methods to more demanding scenarios. Automating the process of testing and evaluation by designing a dense clutter environment generation algorithm (DCEGen) allows us to measure comparative performance of available algorithms. We focus on path-planning algorithms used in an unmanned ground vehicles. The algorithm was implemented and verified using Gazebo simulator.

Experiments are valuable tool of robust control algorithms design, but experiments tend to be expensive. In order to conduct thousands of complex experiments with autonomous car navigation algorithms it is safer and cheaper to start algorithm verification within a simulation, relying on a proper robot model, which preserves physical properties of underlying objects. In this paper we present the design of Avrora Unior mobile robot model, which is a Russian car-like robot with Ackermann steering geometry, and describe the process of modeling its kinematics and dynamics. Robot model was designed within open source robotics framework ROS for Gazebo simulator.

This paper presents the implementation of walking algorithm for small-size humanoid robot ROBOTIS OP3 and its assessment by using force sensitive resistors (FSR). The goal of this work is to provide a simple walking controller based on quasistatic stability and assessment of its performance accuracy with the use of FSR For this purpose, the robot has been retrofitted with ROBOTIS OP2 FSR kit. The servos errors are compared with the center of mass (CoM) position estimated from installed FSR with positioning error analysis.

In this paper we present an algorithm for a mobile robot autonomous return. The algorithm involves a network failure detection module, which is based on analysis of incoming UDP packets. Simultaneous Localization and Mapping (SLAM) and path planning algorithms were used as an integral part of the autonomous return algorithm. The algorithms were integrated into Russian mobile robot Servosila Engineer, and experiments were conducted in order to determine the best configuration of the algorithm parameters.

The paper presents a integral design method to integrate "DFM" (Design for Manufacturing) and "DFV" (Design for Verification), and completes the production system from simulation to actual verification using the SCARA robot arm. In the aspect of kinematics of horizontal joint, the 2D model is established by mathematical derivation and the analysis of the robot arm characteristics using "Jacobian" kinematic, and integrates into the verification design. The electromechanical integration of the proposed system includes a SCARA robot arm, automatic control components, sensors; electrical elements, pneumatic circuit design and software programming for implement. Then user can lead the robotic arm to run the coordinates and movement path with proper accuracy, efficiency and reliability. The program language of the SCARA uses "DRL" (DELTA Robot Language) that is developed by DELTA Company. This research also proposes a design method using automatic palletizing simulate layout for the SCARA robot arm, and verifies the precious positioning of the SCARA robot arm.

Internet of Things (IoT) is one of the most popular research topics. There have been many studies and products about this topic. However, there is few researches about the correctness of data and the mutual support of modules. In this paper, we developed an IoT module with multi-sensor and communication interface. It debugs and confirms the data from multiple modules and sensors using the fusion and the redundant algorithms. It can also sustain or replace a possibly fail IoT module via multiple communication interface. The dynamic security key technology is used to ensure the security of data transmission. Hence the IoT system can be more stable and more secure.

The paper develops a mobile based robot arm using KNRm system. The platform of the mobile based robot arm is built as triangle style. The structure of the robot arm uses the Matrix elements that are manufactured by Barden-Powell International Company. The mobile based robot arm integrates some sensors, three DC servomotor motors, one RC servomotor, a controller, and an image recognition module. The mobile platform embeds a robot arm on the front side. The robot arm is one degree of freedom. The driver device of the robot arm is a RC servomotor. The cargo puts on the plank. The robot arm must rise up and put down the plank. In the experimental results, the mobile based robot arm can search and recognize the assigned plank using image binanzation method and Otsu algorithm by the image recognition system. Finally, the robot arm moves approach to the assigned color plank, and catches the plank moving to the assigned position, and puts down the plank.

Internet of Thing (IOT) is a very hot topic recently, many of the important issues in the field of research. But to the conventional apparatus or systems and network connections, sometimes we need complex modifications or expensive costs. Therefore, this paper using the MCS-51 series single-chip integration of analog, digital signal input, and ETHERNET, WIFI and other communication interface, to develop general-purpose IOT modules. This module can be used to replace existing equipment or devices, or combination use with the original device. We also use the module in a Multi-Agent Method, we can ensure that the module in signal capture or communication failure can be replaced or assisted by other modules. Finally, we can use these modules to build the sensor network.

The article designs a four-joint SCARA robot arm using PLC-based control system. The control system (ASDA-SM) is all in one device to be produced by the DELTA Company, and contains four axis controllers and drivers. The robot arm contains four AC servomotors, four driver devices and a vision system. The PLC-based controller also programs motion commands of the gripper to finish the assigned tasks using Ladder Diagram (LG), Function Block Diagram (FBD), Sequential Function Chart (SFC), Instruction List (LL) and Structure Test (ST). Each driver has been tuned the parameters of the PID controller. The human machine interface (HMI) is a touch panel to be used for the robot arm. Users can control the motion path of any joint, and uses the DOPSoft language to design the human machine interface. In the experimental results, The SCARA robot arm catches a seal, and falls to stamp the assigned positions step by step, and identifies the precious of the robot arm, and moves eight objects to the assigned positions.

The article develops the decision rules to win each set of the Chinese chess game using evaluation algorithm and artificial intelligence method, and uses the mobile robot to be instead of the chess, and presents the movement scenarios using the shortest motion paths for mobile robots.Player can play the Chinese chess game according to the game rules with the supervised computer.The supervised computer decides the optimal motion path to win the set using artificial intelligence method, and controls mobile robots according to the programmed motion paths of the assigned chesses moving on the platform via wireless RF interface.We uses enhance A * searching algorithm to solve the shortest path problem of the assigned chess, and solve the collision problems of the motion paths for two mobile robots moving on the platform simultaneously.We implement a famous set to be called "wild horses run in farm" using the proposed method.First we use simulation method to display the motion paths of the assigned chesses for the player and the supervised computer.Then the supervised computer implements the simulation results on the chessboard platform using mobile robots.Mobile robots move on the chessboard platform according to the programmed motion paths and is guided to move on the centre line of the corridor, and avoid the obstacles (chesses), and detect the cross point of the platform using three reflective IR modules.

A land full of grass can be easily seen all over the world. For example, a golf course, a large playground, garden, waste plowed farmland and wild wasteland, all of above are full of grass. Almost all mowing work are operated by manpower, especially the long grass section. There have been some autonomous mowing robots for short grass up to now. However, there is almost no commodity for long grass mowing in the market. The main possible consideration may be the issue of safety. It is highly possible that a sharp mower blade may cause harm under the condition that the mower is not operated directly by a skilled person. In this paper, we will focus on the mechanism design for an autonomous mowing robot that can cut long grass safely. We will also outline the safety requirements for an autonomous mowing robot for long grass.

This article describes the design of an articulation robot arm with seven joints. The control core of the robot arm is the module-based system built using the Mitsubishi Q series programming logical controller (PLC). The robot arm contains seven AC servomotors, seven driver devices, a vision system and a PLC control system. The PLC-based controller programs the motion trajectory of the gripper to catch or hold the objects and finish the assigned tasks. Kinect system (Asus Xtion Pro-Live, or called RGB-D sensor) acts as the vision system to recognize shape and color of each object. During the experiments, we found that the robot arm recognizes the shape and color of each object, and catches each object moving to the assigned box with the same color.