An intelligent robotic framework for automated assembly

Recent applications of robots for industrial automation have shown significant improvement in manufacturing processes in terms of reducing labor participation, enhancing flexibility, efficiency and quality of the products. However, most applications are limited to point-to-point and noninteractive operations in which the availability of a highly structured setup is a prerequisite. This prompts the vast emergency of researches on intelligent robotics that are aimed to improve the adaptability, flexibility and dexterity so as to enhance the intelligence of industrial robots. This paper investigates the designs of intelligent robotic systems and discusses the proposed criteria required to achieve an intelligent robotic system. A proposed conceptual framework for robotic assembly is then presented that contains two main parts, namely, a robotic state recognizer and a control strategy generator. In addition to these two components, the integration of compliant motion control into the framework will be described. An example of using the proposed framework to develop a robotic assembly system is given.published_or_final_versio

Intelligent systems in manufacturing: current developments and future prospects

Global competition and rapidly changing customer requirements are demanding increasing changes in manufacturing environments. Enterprises are required to constantly redesign their products and continuously reconfigure their manufacturing systems. Traditional approaches to manufacturing systems do not fully satisfy this new situation. Many authors have proposed that artificial intelligence will bring the flexibility and efficiency needed by manufacturing systems. This paper is a review of artificial intelligence techniques used in manufacturing systems. The paper first defines the components of a simplified intelligent manufacturing systems (IMS), the different Artificial Intelligence (AI) techniques to be considered and then shows how these AI techniques are used for the components of IMS

Design of a semi-autonomous modular robotic vehicle for gas pipeline inspection

This paper presents a new solution for inspecting and repairing defects in live gas pipelines. The proposed approach is the development of a modular and semi-autonomous vehicle system. The robotic system has a drive mechanism, capable of navigating and adjusting its orientation in various configurations of pipelines. Other features of the system are cable-free communications, semi-autonomous motion control as well as integration of sensory devices. The robotic system is designed to traverse in 150-300 mm diameter pipes through straight and curved sections, junctions and reducers. The vehicle control and navigation technique is implemented using a two-mode controller consisting of a proportional-integral-derivative (PID) and fuzzy logic control. Unlike other available systems, the vehicle employs proprioceptive sensors to monitor its own states. The fuzzy logic controller is used to evaluate the sensor outputs such as speed, climbing angle and rate of change of climbing angle. This control technique allows the vehicle to drive and adapt in a partially observable gas pipe system. Laboratory experiment results are presented. The paper also describes a cable-free communication method for the system. A brief account of typical pipe environments and currently available inspection tools is presented as background information

Design of a semi-autonomous modular robotic vehicle for gas pipeline inspection

This is an article from the journal, Proceedings of the Institution of Mechanical Engineers, Part I: Journal of Systems and Control Engineering [© IMechE ]. It is also available at: http://journals.pepublishing.com/content/119778This paper presents a new solution for inspecting and repairing defects in live gas pipelines. The proposed approach is the development of a modular and semi-autonomous vehicle system. The robotic system has a drive mechanism, capable of navigating and adjusting its orientation in various configurations of pipelines. Other features of the system are cable-free communications, semi-autonomous motion control as well as integration of sensory devices. The robotic system is designed to traverse in 150-300 mm diameter pipes through straight and curved sections, junctions and reducers. The vehicle control and navigation technique is implemented using a two-mode controller consisting of a proportional-integral-derivative (PID) and fuzzy logic control. Unlike other available systems, the vehicle employs proprioceptive sensors to monitor its own states. The fuzzy logic controller is used to evaluate the sensor outputs such as speed, climbing angle and rate of change of climbing angle. This control technique allows the vehicle to drive and adapt in a partially observable gas pipe system. Laboratory experiment results are presented. The paper also describes a cable-free communication method for the system. A brief account of typical pipe environments and currently available inspection tools is presented as background information

Software tools for the cognitive development of autonomous robots

Robotic systems are evolving towards higher degrees of autonomy. This paper reviews the cognitive tools available nowadays for the fulfilment of abstract or long-term goals as well as for learning and modifying their behaviour.Peer ReviewedPostprint (author's final draft

Mastering Autonomous Assembly in Fusion Application with Learning-by-doing: a Peg-in-hole Study

Robotic peg-in-hole assembly is an essential task in robotic automation research. Reinforcement learning (RL) combined with deep neural networks (DNNs) lead to extraordinary achievements in this area. However, current RL-based approaches could hardly perform well under the unique environmental and mission requirements of fusion applications. Therefore, we have proposed a new designed RL-based method. Furthermore, unlike other approaches, we focus on innovations in the structure of DNNs instead of the RL model. Data from the RGB camera and force/torque (F/T) sensor as the input are fed into a multi-input branch network, and the best action in the current state is output by the network. All training and experiments are carried out in a realistic environment, and from the experiment result, this multi-sensor fusion approach has been shown to work well in rigid peg-in-hole assembly tasks with 0.1mm precision in uncertain and unstable environments

Conference on Intelligent Robotics in Field, Factory, Service, and Space (CIRFFSS 1994), volume 1

The AIAA/NASA Conference on Intelligent Robotics in Field, Factory, Service, and Space (CIRFFSS '94) was originally proposed because of the strong belief that America's problems of global economic competitiveness and job creation and preservation can partly be solved by the use of intelligent robotics, which are also required for human space exploration missions. Individual sessions addressed nuclear industry, agile manufacturing, security/building monitoring, on-orbit applications, vision and sensing technologies, situated control and low-level control, robotic systems architecture, environmental restoration and waste management, robotic remanufacturing, and healthcare applications