Applications of Intelligent Vision in Low-Cost Mobile Robots

With the development of intelligent information technology, we have entered an era of 5G and AI. Mobile robots embody both of these technologies, and as such play an important role in future developments. However, the development of perception vision in consumer-grade low-cost mobile robots is still in its infancies. With the popularity of edge computing technology in the future, high-performance vision perception algorithms are expected to be deployed on low-power edge computing chips. Within the context of low-cost mobile robotic solutions, a robot intelligent vision system is studied and developed in this thesis. The thesis proposes and designs the overall framework of the higher-level intelligent vision system. The core system includes automatic robot navigation and obstacle object detection. The core algorithm deployments are implemented through a low-power embedded platform. The thesis analyzes and investigates deep learning neural network algorithms for obstacle object detection in intelligent vision systems. By comparing a variety of open source object detection neural networks on high performance hardware platforms, combining the constraints of hardware platform, a suitable neural network algorithm is selected. The thesis combines the characteristics and constraints of the low-power hardware platform to further optimize the selected neural network. It introduces the minimize mean square error (MMSE) and the moving average minmax algorithms in the quantization process to reduce the accuracy loss of the quantized model. The results show that the optimized neural network achieves a 20-fold improvement in inference performance on the RK3399PRO hardware platform compared to the original network. The thesis concludes with the application of the above modules and systems to a higher-level intelligent vision system for a low-cost disinfection robot, and further optimization is done for the hardware platform. The test results show that while achieving the basic service functions, the robot can accurately identify the obstacles ahead and locate and navigate in real time, which greatly enhances the perception function of the low-cost mobile robot

Technology Trends and Opportunities for Construction Industry and Lifecycle Management

Master's thesis in for Offshore Technology: Industrial Asset ManagementThe purpose of the report is to highlight methods that can make it easier for the construction industry and industry in general to benefit from new technology. The report is intended as a reference to technological solutions that along with some techniques, can streamline workflow for multiple tasks in planning, design, and operation and maintenance management. The problems focused on is how to: • Simplify the procurement and tracing of documentation • Optimize building stages, design, and Life Cycle Management (LCM) • Provide interactions between disciplines and employees using different software Scientific Platform are based on literature within technology trends. Some history and trends in digital technology are presented. Definition of roles and general terms related to documentation is derived from Norsk Standard and is interpreted on this basis. The report charts the use of individual software and technical setup of digital tools within CAD-engineering (Computer Aided Design), HDS-technology (High Definition Surveying), and gaming technology. This technology combined with cloud-services to support planning, design and management of building stages. Later to support LCM of facilities and businesses' ERP-systems (Enterprise Resource Planning). Use of Robotic Process Automation (RPA) and Artificial Intelligence (AI), for document control tasks. The result of the report is that several suppliers provide services and products accessible through web. Setup and implementation will require some work and knowledge for business and organizations, but the gain largely seems to justify the use of resources for this purpose. Particularly through IOT-interactions (Internet of Things), cloud-services and free downloadable applications that may be considered as a paradigm shift related to the issues in the report. Also, presenting new platforms for engineering phases to support Building Information Modeling processes (BIM). With the use of Algorithmic Editors for encoding between computer programs without the need of data programmer expertise. To streamline workflows, reduce recreation of data, interactions between different software of various user level, and support of AI to optimize designing by adds-on for CAD-engineering (Computer Aided Design). Mobile devices like phones and tablets to support several of solutions and products presented is very accessible. It seems naturally to assume that the vast majority of people are familiar with technology related to smartphone applications for daily use. The use of resources for implementing the presented solutions have not been considered in this report. Some of the equipment presented can be interpreted as relatively expensive. Investment analysis would be sensible. The trend however, shows continues price drops and increased availability. At the same time as the user interface is being improved for both software and digital equipment. The conclusion, is that the construction industry, as well as Facility Management (FM). Within both, public, and private sector, can have much to gain using the technology and techniques presented in the report

Towards a Prototype Platform for ROS Integrations on a Ground Robot

The intent of this work was to develop, evaluate, and demonstrate a prototype robot platform on which ROS integrations could be explored. With observations of features and requirements of existing industrial and service mobile ground robots, a platform was designed and outfitted with appropriate components to enable the most common operational-critical functionalities and account for unforeseen components and features. The resulting Arlo Demonstration Robot accommodates basic mapping, localization, and navigation in both two and three-dimensional space as well as additional safety and teleoperation features. The control system is centered around the Zybo Z7 FPGA SoC hosting a custom hardware design. The platform is validated through an analysis of feature requirements and limitations and additional evaluations of a series of real-world use cases demonstrating high-level behaviors. In order to promote further development, this work serves as detailed documentation of the selection, implementation, and testing of this platform and complements initial binary releases for the Zybo Z7 control system and accompanying source code for the functionalities implemented. This prototype robot stack can be further developed to enable additional capabilities and validate its performance in other real-world scenarios or used as a reference for porting to alternative robot platforms

Case Study on Human-Robot Interaction of the Remote-Controlled Service Robot for Elderly and Disabled Care

The tendency of continuous aging of the population and the increasing number of people with mobility difficulties leads to increased research in the field of Assistive Service Robotics. These robots can help with daily life tasks such as reminding to take medications, serving food and drinks, controlling home appliances and even monitoring health status. When talking about assisting people in their homes, it should be noted that they will, most of the time, have to communicate with the robot themselves and be able to manage it so that they can get the most out of the robot's services. This research is focused on different methods of remote control of a mobile robot equipped with robotic manipulator. The research investigates in detail methods based on control via gestures, voice commands, and web-based graphical user interface. The capabilities of these methods for Human-Robot Interaction (HRI) have been explored in terms of usability. In this paper, we introduce a new version of the robot Robco 19, new leap motion sensor control of the robot and a new multi-channel control system. The paper presents methodology for performing the HRI experiments from human perception and summarizes the results in applications of the investigated remote control methods in real life scenarios

MOTION CONTROL SIMULATION OF A HEXAPOD ROBOT

This thesis addresses hexapod robot motion control. Insect morphology and locomotion patterns inform the design of a robotic model, and motion control is achieved via trajectory planning and bio-inspired principles. Additionally, deep learning and multi-agent reinforcement learning are employed to train the robot motion control strategy with leg coordination achieves using a multi-agent deep reinforcement learning framework. The thesis makes the following contributions: First, research on legged robots is synthesized, with a focus on hexapod robot motion control. Insect anatomy analysis informs the hexagonal robot body and three-joint single robotic leg design, which is assembled using SolidWorks. Different gaits are studied and compared, and robot leg kinematics are derived and experimentally verified, culminating in a three-legged gait for motion control. Second, an animal-inspired approach employs a central pattern generator (CPG) control unit based on the Hopf oscillator, facilitating robot motion control in complex environments such as stable walking and climbing. The robot\u27s motion process is quantitatively evaluated in terms of displacement change and body pitch angle. Third, a value function decomposition algorithm, QPLEX, is applied to hexapod robot motion control. The QPLEX architecture treats each leg as a separate agent with local control modules, that are trained using reinforcement learning. QPLEX outperforms decentralized approaches, achieving coordinated rhythmic gaits and increased robustness on uneven terrain. The significant of terrain curriculum learning is assessed, with QPLEX demonstrating superior stability and faster consequence. The foot-end trajectory planning method enables robot motion control through inverse kinematic solutions but has limited generalization capabilities for diverse terrains. The animal-inspired CPG-based method offers a versatile control strategy but is constrained to core aspects. In contrast, the multi-agent deep reinforcement learning-based approach affords adaptable motion strategy adjustments, rendering it a superior control policy. These methods can be combined to develop a customized robot motion control policy for specific scenarios

Bio-Inspired Robotics

Modern robotic technologies have enabled robots to operate in a variety of unstructured and dynamically-changing environments, in addition to traditional structured environments. Robots have, thus, become an important element in our everyday lives. One key approach to develop such intelligent and autonomous robots is to draw inspiration from biological systems. Biological structure, mechanisms, and underlying principles have the potential to provide new ideas to support the improvement of conventional robotic designs and control. Such biological principles usually originate from animal or even plant models, for robots, which can sense, think, walk, swim, crawl, jump or even fly. Thus, it is believed that these bio-inspired methods are becoming increasingly important in the face of complex applications. Bio-inspired robotics is leading to the study of innovative structures and computing with sensory–motor coordination and learning to achieve intelligence, flexibility, stability, and adaptation for emergent robotic applications, such as manipulation, learning, and control. This Special Issue invites original papers of innovative ideas and concepts, new discoveries and improvements, and novel applications and business models relevant to the selected topics of ``Bio-Inspired Robotics''. Bio-Inspired Robotics is a broad topic and an ongoing expanding field. This Special Issue collates 30 papers that address some of the important challenges and opportunities in this broad and expanding field

Automation and Robotics: Latest Achievements, Challenges and Prospects

This SI presents the latest achievements, challenges and prospects for drives, actuators, sensors, controls and robot navigation with reverse validation and applications in the field of industrial automation and robotics. Automation, supported by robotics, can effectively speed up and improve production. The industrialization of complex mechatronic components, especially robots, requires a large number of special processes already in the pre-production stage provided by modelling and simulation. This area of research from the very beginning includes drives, process technology, actuators, sensors, control systems and all connections in mechatronic systems. Automation and robotics form broad-spectrum areas of research, which are tightly interconnected. To reduce costs in the pre-production stage and to reduce production preparation time, it is necessary to solve complex tasks in the form of simulation with the use of standard software products and new technologies that allow, for example, machine vision and other imaging tools to examine new physical contexts, dependencies and connections