564 research outputs found

    Bio-Inspired Robotics

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    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

    A brief network analysis of Artificial Intelligence publication

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    In this paper, we present an illustration to the history of Artificial Intelligence(AI) with a statistical analysis of publish since 1940. We collected and mined through the IEEE publish data base to analysis the geological and chronological variance of the activeness of research in AI. The connections between different institutes are showed. The result shows that the leading community of AI research are mainly in the USA, China, the Europe and Japan. The key institutes, authors and the research hotspots are revealed. It is found that the research institutes in the fields like Data Mining, Computer Vision, Pattern Recognition and some other fields of Machine Learning are quite consistent, implying a strong interaction between the community of each field. It is also showed that the research of Electronic Engineering and Industrial or Commercial applications are very active in California. Japan is also publishing a lot of papers in robotics. Due to the limitation of data source, the result might be overly influenced by the number of published articles, which is to our best improved by applying network keynode analysis on the research community instead of merely count the number of publish.Comment: 18 pages, 7 figure

    A Biomimetic steering robot for Minimally invasive surgery application

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    International audienceMinimally Invasive Surgery represents the future of many types of medical inter- ventions such as keyhole neurosurgey or transluminal endoscopic surgery. These procedures involve insertion of surgical instruments such as needles and endoscopes into human body through small incision/ body cavity for biopsy and drug delivery. However, nearly all surgical instruments for these procedures are inserted manually and there is a long learning curve for surgeons to use them properly. Many research efforts have been made to design active instruments (endoscope, needles) to improve this procedure during last decades. New robot mechanisms have been designed and used to improve the dexterity of current endoscope. Usually these robots are flexible and can pass the constrained space for fine manipulations. In recent years, a con- tinuum robotic mechanism has been investigated and designed for medical surgery. Those robots are characterized by the fact that their mechanical components do not have rigid links and discrete joints in contrast with traditional robot manipula- tors. The design of these robots is inspired by movements of natural animals such as tongues, elephant trunks and tentacles. The unusual compliance and redundant degrees of freedom of these robots provide strong potential to achieve delicate tasks successfully even in cluttered and unstructured environments. This chapter will present a complete application of a continuum robot for Mini- mally Invasive Surgery of colonoscopy. This system is composed of a micro-robotic tip, a set of position sensors and a real-time control system for guiding the explo- ration of colon. Details will be described on the modeling of the used pneumatic actuators, the design of the mechanical component, the kinematic model analysis and the control strategy for automatically guiding the progression of the device inside the human colon. Experimental results will be presented to check the perfor- mances of the whole system within a transparent tube

    Selected Papers from IEEE ICASI 2019

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    The 5th IEEE International Conference on Applied System Innovation 2019 (IEEE ICASI 2019, https://2019.icasi-conf.net/), which was held in Fukuoka, Japan, on 11–15 April, 2019, provided a unified communication platform for a wide range of topics. This Special Issue entitled “Selected Papers from IEEE ICASI 2019” collected nine excellent papers presented on the applied sciences topic during the conference. Mechanical engineering and design innovations are academic and practical engineering fields that involve systematic technological materialization through scientific principles and engineering designs. Technological innovation by mechanical engineering includes information technology (IT)-based intelligent mechanical systems, mechanics and design innovations, and applied materials in nanoscience and nanotechnology. These new technologies that implant intelligence in machine systems represent an interdisciplinary area that combines conventional mechanical technology and new IT. The main goal of this Special Issue is to provide new scientific knowledge relevant to IT-based intelligent mechanical systems, mechanics and design innovations, and applied materials in nanoscience and nanotechnology

    Rapid acceleration of legged robots: a pneumatic approach

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    For robotics to be useful to the public in a multifaceted manner, they need to be both legged and agile. The legged constraint arises as many environments and systems in our world are tailored to ablebodied adults. Therefore, a practically useful robot would need to have the same morphology for maximum efficacy. For robots to be useful in these environments, they need to perform at least as well as humans, therefore presenting the agility constraint. These requirements have been out of reach of the field until recently. The aim of this thesis was to design a planar monopod robot for rapid acceleration manoeuvres, that could later be expanded to a planar quadruped robot. This was achieved through a hybrid electric and pneumatic actuation system. To this end, modelling schemes for the pneumatic cylinder were investigated and verified with physical experiments. This was done to develop accurate models of the pneumatic system that were later used in simulation to aid in the design of the platform. The design of the platform was aided through the use of Simulink to conduct iterative testing and multivariate evaluations using Monte Carlo simulation methods. Once the topology of the leg was set, the detail design was conducted in Solidworks and validated with its built in simulation functions. In addition to the mechanical design of the platform, a specialist boom was designed. The design needed to compensate for the forces the robot exerts on the boom as well as the material constraints on the boom. This resulted in the development of a cable-stayed, four bar mechanism boom system. An embedded operating system was created to control the robot and take in and fuse sensor inputs. This was run using multiple sensors, sub-controllers and microcontrollers. Sensor fusion for the system was done using a Kalman Filter to improve readings and estimate unmeasured states of the robot. This Kalman Filter took LiDAR and accelerometer readings as inputs to the system to produce a subcentimetre accurate position measure for the system. Finally, the completed platform was validated using fixed-body forward hopping tests. These tests showed a significant degree of similarity to the simulated results and therefore validated the design process

    State Estimation for Legged Robots - Consistent Fusion of Leg Kinematics and IMU

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    This paper introduces a state estimation framework for legged robots that allows estimating the full pose of the robot without making any assumptions about the geometrical structure of its environment. This is achieved by means of an Observability Constrained Extended Kalman Filter that fuses kinematic encoder data with on-board IMU measurements. By including the absolute position of all footholds into the filter state, simple model equations can be formulated which accurately capture the uncertainties associated with the intermittent ground contacts. The resulting filter simultaneously estimates the position of all footholds and the pose of the main body. In the algorithmic formulation, special attention is paid to the consistency of the linearized filter: it maintains the same observability properties as the nonlinear system, which is a prerequisite for accurate state estimation. The presented approach is implemented in simulation and validated experimentally on an actual quadrupedal robot

    \u3cem\u3eGRASP News\u3c/em\u3e: Volume 9, Number 1

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    The past year at the GRASP Lab has been an exciting and productive period. As always, innovation and technical advancement arising from past research has lead to unexpected questions and fertile areas for new research. New robots, new mobile platforms, new sensors and cameras, and new personnel have all contributed to the breathtaking pace of the change. Perhaps the most significant change is the trend towards multi-disciplinary projects, most notable the multi-agent project (see inside for details on this, and all the other new and on-going projects). This issue of GRASP News covers the developments for the year 1992 and the first quarter of 1993

    Combining Sensors and Multibody Models for Applications in Vehicles, Machines, Robots and Humans

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    The combination of physical sensors and computational models to provide additional information about system states, inputs and/or parameters, in what is known as virtual sensing, is becoming increasingly popular in many sectors, such as the automotive, aeronautics, aerospatial, railway, machinery, robotics and human biomechanics sectors. While, in many cases, control-oriented models, which are generally simple, are the best choice, multibody models, which can be much more detailed, may be better suited to some applications, such as during the design stage of a new product
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