A memristor-based hybrid analog-digital computing platform for mobile robotics.

The construction of a smart autonomous mobile robot system that can operate in an anonymous environment can be difficult. Building an autonomous mobile robot requires collecting data from sensors and cameras in order to recognize the surrounding environment, get knowledge of existing landmarks, and figure out its position and orientation. Many research studies have been carried out in recent years providing algorithms for achieving autonomous motion of mobile robot systems and object detection. The most common platform utilized for robot motion design is ROS (Robot Operating System) and for object detection YOLO (You Only Look Once) is a common choice. Additionally, the autonomous system needs motion planning in a systematic way to avoid obstacles by using LIDAR or other sensing methods generating the feedback signals required for control of motion around occupied spaces. One of the most effective and versatile feedback systems for mobile robot control can be constructed using visual feedback, which relies on a high-resolution camera that processes the image in real-time and the result is fed back to the control system for decision making. Visual feedback can be employed alone without sensors for feedback control of autonomous mobile robots, and it can be used for multiple tasks like path planning, obstacle avoidance, object detection, object recognition in addition to motion control. In this research, results of design and construction of an autonomous mobile rescue robot for finding victims through video data are presented. It is aimed to find victims via applying video as a data collection and feedback generation tool in the autonomous mobile robot control system. The visual feedback and YOLO v3 are used not only for finding victims but also for motion control. Our autonomous mobile robot is designed to move smoothly to the victim's direction and avoids obstacles by using ROS Global Planner. The robot is tested in multiple scenarios in different locations, various obstacle and victim numbers, and satisfactory results with good performances are obtained.

Stability analysis and motion planning strategies with fuzzy coordinator and learning for mobile base robotic part macro/micro-assembly tasks

We present path-planning techniques for a multiple mobile robot system. The mobile robot has the shape of a cylinder, and its diameter, height, and weight are 8 cm, 15 cm, and 1.5 kg, respectively. The controller of the mobile robot is an MCS-51 chip, and it acquires detection signals from sensors through I/O pins. It receives commands from the supervising computer via a wireless RF interface, and transmits the status of the robots to the supervising computer via a wireless RF interface. The mobile robot system is a module-based system, and contains a controller module (including two DC motors and drivers), an obstacle detection module, a voice module, a wireless RF module, an encoder module, and a compass detection module. We propose an evaluation method to arrange the position of the multiple mobile robot system, and develop a path-planning interface on the supervising computer. In the experimental results, the mobile robots were able to receive commands from the supervising computer, and to move their next positions according to the proposed method.

Robotics is a scientific discipline which includes the operation and development of robots and other fields of computer science, as well as electrical and mechanical engineering and high-performance modular control systems. This paper reports the first results of a research project that uses a previously developed MES - Modular Electronic System for autonomous mobile robots and for developing robots to use the MES in other scientific applications. This approach offers the ability to build a scalable and flexible control system with only a few modules. A novel feature of our approach is its modular integration of electronics with the ability to multitask, which can be adapted for particular applications. We demonstrate the robustness of this approach in controlling an indoor mobile robot for the EUROBOT 2009 and 2010.

An Electric Differential System for an Autonomous Mobile Robot Based on Neural Network Model

The research on two-wheeled inverted pendulum (T-WIP) mobile robots or commonly known as balancing robots have gained momentum over the last decade in a number of robotic laboratories around the world. This paper describes the hardware design of such a robot. The objective of the design is to develop a T-WIP mobile robot to be used as flexible platform comprises of embedded unstable linear plant intended for research and teaching purposes. Issues such as selection of actuators and sensors, signal processing units, modeling and control scheme was addressed and discussed. The system is then tested using a well-known pole-placement state feedback controller to verify its functionality.

In this study, we present a socially aware navigation framework for mobile service robots by integrating the systems proposed in our previous studies into a completed mobile robot navigation system, including the human detection and tracking system that is used to detect and track humans; the encoder and laser-based localization and mapping system that is used to determine the position of the robot in the environment; the approaching pose estimation system that is used to estimate the approaching pose of the robot to the human; and the social timed elastic band-based motion planning system that is used to socially navigate the mobile robots to approach the human. In addition, in the paper we describe in detail the motor control system and the design of our mobile robot platform, which is then utilized to conduct experiments in the real-world environments. We verify the feasibility and usefulness of the proposed socially aware robot navigation framework through a series of experiments in a corridor-like environment. The experimental results show that our proposed framework is able to drive the mobile robots to both avoid and approach the humans, providing the safety and comfort for the humans and socially acceptable behaviors for the mobile service robots in the dynamic social environments.

Currently, mobile robots are developing rapidly and are finding numerous applications in the industry. However, several problems remain related to their practical use, such as the need for expensive hardware and high power consumption levels. In this study, we build a low-cost indoor mobile robot platform that does not include a LiDAR or a GPU. Then, we design an autonomous navigation architecture that guarantees real-time performance on our platform with an RGB-D camera and a low-end off-the-shelf single board computer. The overall system includes SLAM, global path planning, ground segmentation, and motion planning. The proposed ground segmentation approach extracts a traversability map from raw depth images for the safe driving of low-body mobile robots. We apply both rule-based and learning-based navigation policies using the traversability map. Running sensor data processing and other autonomous driving components simultaneously, our navigation policies perform rapidly at a refresh rate of 18 Hz for control command, whereas other systems have slower refresh rates. Our methods show better performances than current state-of-the-art navigation approaches within limited computation resources as shown in 3D simulation tests. In addition, we demonstrate the applicability of our mobile robot system through successful autonomous driving in an indoor environment.

This article presents experimental studies of fuzzy logic application to control a two-wheel mobile robot(TWMR) system. The TWMR system is composed of two systems, an inverted pendulum system and a mobile robot system. Although linear controllers can stabilize the TWMR, fuzzy controllers are expected to have robustness to uncertainties so that the resulting performances are expected to be better. Nominal fuzzy rules are used to control balance and position of TWMR. Fuzzy logic is embedded on a DSP chip to control the TWMR. Balancing performances of the PID controller and the fuzzy controller under disturbances are compared through extensive experimental studies.

A dead reckoning system for a wheeled mobile robot was designed, and the method for robot’s pose estimation in the 3D environments was presented on the basis of its rigid-body kinematic equations. After analyzing the locomotion architecture of mobile robot and the principle of proprioceptive sensors, the kinematics model of mobile robot was built to realize the relative localization. Considering that the research on dead reckoning of mobile robot was confined to the 2 dimensional planes, the locomotion of mobile robot in the 3 coordinate axis direction was thought over in order to estimate its pose on uneven terrain. Because the computing method in a plane is rather mature, the calculation in height direction is emphatically represented as a key issue. With experimental results obtained by simulation program and robot platform, the position of mobile robot can be reliably estimated and the localization precision can be effectively improved, so the effectiveness of this dead reckoning system is demonstrated.

The goal of this research was to develop a fuzzy obstacle avoidance system for an autonomous mobile robot using IR detection sensors. This paper presents implemented control architecture for behavior-based mobile robot. The mobile robot is able to interact with an unknown environment using a reactive strategy determined by sensory information. Current research in robotics aims to build autonomous and intelligent robots, which can plan its motion in a dynamic environment. Autonomous mobile robots are increasingly used in well structured environment such as warehouses, offices and industries. Fuzzy behavior able to make inferences is well suited for mobile robot navigation because of the uncertainty of the environment. A rule-based fuzzy controller with reactive behavior was implemented and tested on a two wheels mobile robot equipped with infrared sensors to perform collision-free navigation. The experimental results have shown that the proposed architecture provides an efficient and flexible solution for small wheeled mobile robots.

The subject of this research is the technology of management of mobile robot groups in the concept of Industry 4.0 and its composition. The purpose of this article is to find ways to implement an effective strategy for building and managing mobile robotic platforms in Warehousing, as a key tool of Lean Production. To achieve this goal, it is necessary to solve the following tasks: to analyze the management of supply chains in Smart Manufacturing, within Industry 4.0 and its impact on achieving the goals of Lean Production; to study the evolution of technologies used in Warehousing in the dynamics of the Industrial Revolution; to analyze the evolution of Warehouse Management Systems (WMS) as one of the most important components on the basis of which the requirements for automation of Warehousing automation in Smart Manufacturing with group management of mobile robotic platforms are implemented and achieved; to compare the impact of the technologies used by Warehousing 4.0 and Warehouse Management Systems on the key indicators of Lean Production. Results: One of the promising ways to achieve the effectiveness of the implementation of Lean Production tools in WMS systems is the use of Collaborative Robot System technology, which makes it possible to ensure a high density of product storage in Warehousing. However, modern mobile robotic platforms have their limitations both in the methods of loading and unloading products, and in the design. Therefore, the authors see the task in improving the design of mobile robotic platforms, which will develop a new intelligent group method of loading and unloading products, increasing the storage density for a variety of goods. Conclusions: The paper compares the impact of Warehousing 4.0 and Warehouse Management Systems on key Lean Production tools, which shows how the introduction of new group management technologies for robotic platforms in Warehousing 4.0 and Warehouse Management Systems (WMS) affects the effectiveness of Lean Production tools such as Heijunka, Just-in-time, 5S. This suggests that the introduction of new models and methods of managing complex warehouses with high density and chaotic storage of products, through the use of mobile robotic autonomous systems, will significantly optimize the process of supply chain management in Smart Manufacturing.

This manuscript presents a universal control law for a class of complex dynamic systems, such as mobile robots. The trajectory tracking problem is among the major problems in the field of robotics. The proposed universal control law solves the trajectory tracking problem of mobile robots. Despite a large body of research on developing robot's control laws conducted in the literature, the dynamic effects of robots are often not taken into consideration while deriving control laws that define their trajectories. In most cases, the robot's trajectory tracking and/or stabilization problems are addressed based on its kinematic model due to simplicity. Therefore, the need for a universal control law based on the robot's dynamic and/or kinematic model is significant. Even though the feedback control theory is well-established in the field of robotics, the control laws for dynamic systems are typically more complex than system models themselves. Furthermore, control laws are required to be adapted depending on models of different mobile robot systems. Here, the development of universal control law is underscored, i.e., the paper is aimed at developing universal dynamic tracking control law that solves the trajectory tracking problem of a class of mobile robots. The controller is tested through a set of computer simulations using a differential drive mobile robot operating in an indoor planar environment.

Increasing population age demands more services in healthcare domain. It has been shown that mobile robots could be a potential solution to home biomonitoring for the elderly. Through our previous studies, a mobile robot system that is able to track a subject and identify his daily living activities has been developed. However, the system has not been tested in any home living scenarios. In this study we did a series of experiments to investigate the accuracy of activity recognition of the mobile robot in a home living scenario. The daily activities tested in the evaluation experiment include watching TV and sleeping. A dataset recorded by a distributed distance-measuring sensor network was used as a reference to the activity recognition results. It was shown that the accuracy is not consistent for all the activities; that is, mobile robot could achieve a high success rate in some activities but a poor success rate in others. It was found that the observation position of the mobile robot and subject surroundings have high impact on the accuracy of the activity recognition, due to the variability of the home living daily activities and their transitional process. The possibility of improvement of recognition accuracy has been shown too.

Mobile robot motion control is simplified to a DC motor motion control that may include gear system. The simplest and widespread approach to control the mobile robot motion is the differential drive style, it consists of two in-lines with each a DC motor. Both DC motors are independently powered so the desired movements will rely on how these two DC motors are commanded. Thedevelop design, model and control of Mechatronics mobile robotic system is presented in this paper. The developed robotic system is intended for research purposes as well as for educational process. The model of proposed mobile robot was created and verified using MATLAB-Simulink software.