AdaptPack Studio: an automated intelligent framework for offline factory programming

Artificial intelligence (AI), imitation learning, big data, cloud and distributed computing, robotics cells, and information communication technology, are some of the key tools and elements of the future digital and smart manufacturing facility. There are a number of challenges that digital and smart manufacturing is facing, especially with the complication of AI (i.e., machine, deep and cognitive learning) algorithms, great amount of data to process, and essential complex coding required, which makes immediate changes needed in manufacturing facilities not straightforward. This is notable in small manufacturing cells which is an integrated part of future smart factories such manufacturing facilities are usually needed some annual and regular updates to meet the update in the design specifications of next generation of products. Imitation learning is offering a great opportunity to overcome these challenges and simplify such complications, where human skills, ability to perform specific tasks, knowledge, and talent could be transferred. This is conveying the knowledge, and skills transfer using imitation learning. However, smart manufacturing and industrial revolution needs robotics cells that has skills beyond this, especially when it comes to process optimisation. Therefore, deep imitation learning could come in to help in the development of self-learning robotic systems and cells. Of course with the powerful tools such as distributed computing, blockchain, cloud computing, edge computing, and 5G the collaboration between such self-learning robotic cells will be possible. This will certainly not eliminate human existence but will enhance the manufacturing environment. This paper is focused on presenting the outcomes of CAD simulation and modelling phase of the ongoing research programme that focused on developing a self-learning robotic system using imitation learning. CAD tools have been used and some initial results is presented. Further work is still undertaken, and this will focus on learning from more than one expert, optimisation, impact of dynamic manufacturing environment.

Modern manufacturing systems consist of a sequence of robotic systems, such as robotic cells, which are widely used in the industry. As they become commonplace and play important roles in modern industrial production, efficient modelling and use of robotic cells become a necessity. Robotization brings many measurable benefits. It enables effective utilization of both human resources and the possessed machine park and thus contributing to the improvement of product quality and efficiency. Industrial robots not only increase the growth of productivity, by replacing man in monotonous works, requiring enormous, not achievable for human precision but above all ensure the accuracy and repeatability of the product quality. Appropriate design and modelling of robotic manufacturing systems are crucial in the efficient integration of work cell components and proper maintenance of robotic production systems. Therefore, new solutions for programming environments in industrial applications are sought which not only allow reprogramming of industrial robots but also enable the virtual design of new production lines, which in turn allows the faster introduction of higher quality products. This article presents the modelling and programming of robotic work cells in the Siemens Process Simulate environment.

Companies are increasingly being forced by market demands to increase the competitiveness of their products in regard to price, quality and delivery time. Development, both of product and production, is the key word in achieving this goal. This paper focuses on the following related subject: cost-effective design, with applications to robotic assembly cells. Against this background, a total productivity model is introduced, which allows an opinion to be formed about the performance of robotic assembly cells during the conceptual stage of the design process.

In this paper, a computational approach to investigate the feasibility of using Smart Timoshenko beam (STB) for underwater locomotion is presented. The main objective of the current study is to understand different thrust producing mechanisms, namely flapping and undulatory modes of locomotion and to identify the critical parameters, such as body length, flexural stiffness and tail beat frequency affecting the locomotion. The thrust for different modes of locomotion with a variation in Young’s modulus and moment of inertia for the STB has been calculated. The results will help improve the understanding of thrust generation in both flapping and undulatory modes which are essential in the design and development of the bio-inspired robotic systems for underwater locomotion.

The present work shows the design and development of a dexterous anthropomorphic robotic hand that meets the requirements of size and similar movement range of a human hand. The main purpose of this project is to support students and researchers to improve their development times. This work gives a close description of how the mechanical system was conceived, how the problems were solved and the processing capacity of the electronic system and its general characteristics.

ヒューマノイドにおける先読み行動システムの構成法に関する研究(ヒューマノイド2)

Robotic systems are now an essential part of the modern world, be it industries, bio-medicals, hospitality etc. Robotic systems involve in-depth, procedural mechanisms that include designing & mathematical modeling of the system, followed by simulation of the designed system to check its working before development and eventually developing robotic systems utilizing the control principles for efficient and error free implementation. The chapter focuses on advancements in the aspects of design, modeling, development and control principles of robotic systems which enhance their efficacy.

Robotics is rapidly expanding into human environments and vigorously engaged in its new emerging challenges. Interacting, exploring, and working with humans, the new generation of robots will increasingly touch people and their lives. The successful introduction of robots in these environments will rely on the development of competent and practical systems that are dependable, safe, and easy to use. To effectively work and cooperate with a person, robots must display abilities and skills that are compatible with those of humans. The discussion focuses on the ongoing effort for the design and development of human-friendly robotic systems that can safely and effectively interact and work with humans.

Inadequate visual and force feedback while navigating surgical tools elevate the risk of endovascular procedures. It also poses occupational hazard due to repeated exposure to X-rays. A teleoperated robotic system that augments surgeon's actions is a solution. We have designed and developed an endovascular robotic system that augments surgeon's actions using conventional surgical tools, as well as generates feedback in order to ensure safety during the procedure. The reaction force from vasculature is estimated from motor current that drives the surgical tool. Calibration required for force estimation is based on bilevel optimization. Input shaping is used in conjunction with a cascaded controller to avoid large responses due to faster inputs and to track tool position. The design, realization, and testing of our system are presented. The responses of the system in comparison with the dynamics model is similar vis-à-vis the same input commands. Any error in the position tracking is reduced by the cascaded controller. Phase-portrait analysis of the system showed that the system is stable. The reaction force estimation is validated against load cell measurements. The safety mechanism in the events of excessive reaction forces while interacting with vasculature is demonstrated. Our system is a step toward intelligent robots that can assist surgeons during endovascular procedures by monitoring and alerting the surgeons regarding detrimental parameters. It arrests any unintended excursions of the surgical tools or surgeon's actions. This will also eliminate the need for surgeons to be in radiation environment.

Aim at solving the main problems of complexity and mechanism rigidity in the design and development of gorilla robot system, the modular combinational design method is introduced to the design of gorilla robot. Based on series joint unit with high rigidity and large output, a modular combinational gorilla robot is designed. The opening control system of the gorilla robot is composed of RS485 and intelligent drive and control modular. The developed gorilla robot system has characteristics of multiple motion ways, lighter weight - about 35kg, minitype - minimal standing height of 0.89m, integration and modular combination

This paper proposes and implements a teleoperation system based on a SCARA-type isomorphic robotic arm, which is able to improve the synchronization and accuracy of the remote control of the robotic arm in high-risk environments. Heterogeneous teleoperation systems are often used in high-risk scenarios where control is not intuitive due to inconsistent operation and delayed response, joint positions are difficult to manipulate directly. In order to overcome the limitations of heterogeneous teleoperation systems in these aspects, the system is designed with a master-slave integrated isomorphic control scheme, which allows the operator's actions to be accurately reproduced at the remote end. In the mechanical design of the system, the end joints are added to the scara robotic arm to solve the problem of insufficient workspace and flexibility; in the software design, the multi-task scheduling mechanism based on real-time operating system (RTOS) is adopted to ensure that the system can respond efficiently to complex tasks; In the algorithm design, the packet first and last frame check design is adopted to ensure that the system will not generate incorrect operation due to signal interference. Experimental results show that the remote operation system shows excellent stability and environmental adaptability in complex environments, and is expected to become a reliable solution for remote precision operation.

Autonomous robot navigation in austere environments is critical to missions like “search and rescue”, yet it remains difficult to achieve. The recent DARPA Subterranean Challenge (SubT) highlights prominent challenges including GPS-denied navigation through rough terrains, rapid exploration in large-scale three-dimensional (3D) space, and interrobot coordination over unreliable communication. Solving these challenges requires both mechanical resilience and algorithmic intelligence. Here, we present our approach that leverages a fleet of custom-built heterogeneous robots and an autonomy stack for robust navigation in challenging environments. Our approach has demonstrated superior navigation performance in the SubT Final Event, resulting in the fastest traversal and most thorough exploration of the environment, which won the “Most Sectors Explored Award.” This paper details our approach from two aspects: mechanical designs of a marsupial ground-and-aerial system to overcome mobility challenges and autonomy algorithms enabling collective rapid exploration. We also provide lessons learned in the design, development, and deployment of complex but resilient robotic systems to overcome real-world navigation challenges.

Cleaning high-altitude building windows is traditionally a high-risk task for human workers due to the danger of falls. To enhance safety in facade cleaning and similar tasks, the development of window-cleaning robots has become increasingly essential. However, current robots face challenges in navigating exoskeleton structures due to obstructive beams, limiting their application. This article proposes a novel biped window-cleaning robotic system (BWCRS) designed for exoskeleton structures. The system comprises two key components: a multifunctional biped climbing robot (BCR) and a specialized cleaning robot. The BCR is adept at overcoming obstacles inherent in exoskeleton structures and transitioning across various inclined window surfaces. The BCR adopts a symmetrical construction, and the ends of the feet are equipped with vacuum suction cups and electromagnets, which can switch between different actuators at the geometric base and end of the system. The system is further enhanced by air pressure sensors that monitor the suction cup adhesion in real time, ensuring stable operation. A crucial functionality of the BCR is its manipulation mode, guided by a visual camera. This mode enables precise location and manipulation of the cleaning robot, ensuring effective coverage of all window areas. The mechanical design and mathematical modeling of the BWCRS are thoroughly examined, demonstrating its robust window-cleaning capabilities. The experimental results reveal that the proposed BCR has a favorable window-climbing and manipulation ability and that the BWCRS has a favorable cleaning effect on the exoskeleton-structure windows. Note to Practitioners—This paper is motivated by the problem of window-cleaning for exoskeleton structures, but it also applies to solving window maintenance and inspection. Previous window-cleaning robots were mainly aimed at the facades or surfaces with low obstacles that cannot be applied directly to exoskeleton-structured windows. This paper proposes an exoskeleton-structure window-cleaning method based on a biped window-climbing robot and a cleaning robot. The biped robot can climb over obstacles on the exoskeleton structures and manipulate the cleaning robot to different cleaning areas. Here, we introduce the biped window-climbing robot from the perspective of mechanical design and mathematical kinematics. We then demonstrate multiple obstacle-crossing motion modes of the biped window-climbing robot. Combined with visual-based manipulation, the window-cleaning process for the exoskeleton structures by a biped window-climbing robot integrated with a cleaning robot is demonstrated. The results verify that the proposed design can complete window-cleaning tasks on exoskeleton structures.

This paper presents the design, hardware development, and functional evaluation of an accelerometer-driven gesture controlled robotic system based on low-cost and easily deployable electronics.The system employs an Arduino Nano as the primary controller, an RF 433 MHz communication link, and HT12E/HT12D encoderdecoder IC's to establish reliable wireless data transfer between the transmitter and the robotic vehicle.An accelerometer mounted on the hand of the user enables intuitive gesture-based commands that are converted into motion actions through programmed control logic.The robot chassis, driven by a dual-relay actuation unit, performs linear and directional movements based solely on the user's hand tilt.The work demonstrates how simple sensing and wireless communication technologies can be combined to create an efficient humanmachine interaction platform suitable for assistive robotics, automation, and educational applications.

Unskillful operation and rough handling of conventional colonoscope, especially at the sigmoid colon, may lead to perforation or splitting the colon wall. Thus, it is crucial to develop autonomous or semi-autonomous colonoscopes that do not require physical force by the doctors for their motions. In this paper, we report the design and development of a colonoscopic robot system that has a locomotive function based on inchworm-like motion, with a hollow body and a steering system that consists of three pneumatic bellows of 7mm diameter, each located 120 ◦ apart from the others at the head part. The steering device can bend up to approximately 90 ◦ . In order to evaluatethe performance of the colonoscopic robot, in-vitro tests and in-vivo tests were carried out. The experimental results show the feasibility of the prototype colonoscopic robot being used for diagnosis and treatments in colon.