918 resultados para ROBOTIC ARM
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Bone-mounted robotic guidance for pedicle screw placement has been recently introduced, aiming at increasing accuracy. The aim of this prospective study was to compare this novel approach with the conventional fluoroscopy assisted freehand technique (not the two- or three-dimensional fluoroscopy-based navigation). Two groups were compared: 11 patients, constituting the robotical group, were instrumented with 64 pedicle screws; 23 other patients, constituting the fluoroscopic group, were also instrumented with 64 pedicle screws. Screw position was assessed by two independent observers on postoperative CT-scans using the Rampersaud A to D classification. No neurological complications were noted. Grade A (totally within pedicle margins) accounted for 79% of the screws in the robotically assisted and for 83% of the screws in the fluoroscopic group respectively (p = 0.8). Grade C and D screws, considered as misplacements, accounted for 4.7% of all robotically inserted screws and 7.8% of the fluoroscopically inserted screws (p = 0.71). The current study did not allow to state that robotically assisted screw placement supersedes the conventional fluoroscopy assisted technique, although the literature is more optimistic about the former.
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The authors present the four-arm single docking full robotic surgery to treat low rectal cancer. The eight main operative steps are: 1- patient positioning; 2- trocars set-up and robot docking; 3- sigmoid colon, left colon and splenic flexure mobilization (lateral-to-medial approach); 4-Inferior mesenteric artery and vein ligation (medial-to-lateral approach); 5- total mesorectum excision and preservation of hypogastric and pelvic autonomic nerves (sacral dissection, lateral dissection, pelvic dissection); 6- division of the rectum using an endo roticulator stapler for the laparoscopic performance of a double-stapled coloanal anastomosis (type I tumor); 7- intersphincteric resection, extraction of the specimen through the anus and lateral-to-end hand sewn coloanal anastomosis (type II tumor); 8- cylindric abdominoperineal resection, with transabdominal section of the levator muscles (type IV tumor). The techniques employed were safe and have presented low rates of complication and no mortality.
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We investigated the feasibility and safety of four-arm robotic lung lobectomy in patients with lung cancer and described the robotic lobectomy technique with mediastinal lymph node dissection.
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BACKGROUND: Several clinical studies on chronic stroke conducted with end-effector-based robots showed improvement of the motor function in the affected arm. Compared to end-effector-based robots, exoskeleton robots provide improved guidance of the human limb and are better suited to train task-oriented movements with a large range of motions. OBJECTIVE: To test whether intensive arm training with the arm exoskeleton ARMin I is feasible with chronic-stroke patients and whether it improves motor function in the paretic arm. METHODS: Three single cases with chronic hemiparesis resulting from unilateral stroke (at least 14 months after stroke). A-B design with 2 weeks of multiple baseline measurements (A), 8 weeks of training (B) with repetitive measurements and a follow-up measurement 8 weeks after training. The training included shoulder and elbow movements with the robotic rehabilitation device ARMin I. Two subjects had three 1-hour sessions per week and 1 subject received five 1-hour sessions per week. The main outcome measurement was the upper-limb part of the Fugl-Meyer Assessment (FMA). RESULTS: The ARMin training was well tolerated by the patients, and the FMA showed moderate, but significant improvements for all 3 subjects (p < 0.05). Most improvements were maintained 8 weeks after discharge. CONCLUSIONS: This study indicates that intensive training with an arm exoskeleton is feasible with chronic-stroke patients. Moderate improvements were found in all 3 subjects, thus further clinical investigations are justified.
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In practice the robotic manipulators present some degree of unwanted vibrations. The advent of lightweight arm manipulators, mainly in the aerospace industry, where weight is an important issue, leads to the problem of intense vibrations. On the other hand, robots interacting with the environment often generate impacts that propagate through the mechanical structure and produce also vibrations. In order to analyze these phenomena a robot signal acquisition system was developed. The manipulator motion produces vibrations, either from the structural modes or from endeffector impacts. The instrumentation system acquires signals from several sensors that capture the joint positions, mass accelerations, forces and moments, and electrical currents in the motors. Afterwards, an analysis package, running off-line, reads the data recorded by the acquisition system and extracts the signal characteristics. Due to the multiplicity of sensors, the data obtained can be redundant because the same type of information may be seen by two or more sensors. Because of the price of the sensors, this aspect can be considered in order to reduce the cost of the system. On the other hand, the placement of the sensors is an important issue in order to obtain the suitable signals of the vibration phenomenon. Moreover, the study of these issues can help in the design optimization of the acquisition system. In this line of thought a sensor classification scheme is presented. Several authors have addressed the subject of the sensor classification scheme. White (White, 1987) presents a flexible and comprehensive categorizing scheme that is useful for describing and comparing sensors. The author organizes the sensors according to several aspects: measurands, technological aspects, detection means, conversion phenomena, sensor materials and fields of application. Michahelles and Schiele (Michahelles & Schiele, 2003) systematize the use of sensor technology. They identified several dimensions of sensing that represent the sensing goals for physical interaction. A conceptual framework is introduced that allows categorizing existing sensors and evaluates their utility in various applications. This framework not only guides application designers for choosing meaningful sensor subsets, but also can inspire new systems and leads to the evaluation of existing applications. Today’s technology offers a wide variety of sensors. In order to use all the data from the diversity of sensors a framework of integration is needed. Sensor fusion, fuzzy logic, and neural networks are often mentioned when dealing with problem of combing information from several sensors to get a more general picture of a given situation. The study of data fusion has been receiving considerable attention (Esteban et al., 2005; Luo & Kay, 1990). A survey of the state of the art in sensor fusion for robotics can be found in (Hackett & Shah, 1990). Henderson and Shilcrat (Henderson & Shilcrat, 1984) introduced the concept of logic sensor that defines an abstract specification of the sensors to integrate in a multisensor system. The recent developments of micro electro mechanical sensors (MEMS) with unwired communication capabilities allow a sensor network with interesting capacity. This technology was applied in several applications (Arampatzis & Manesis, 2005), including robotics. Cheekiralla and Engels (Cheekiralla & Engels, 2005) propose a classification of the unwired sensor networks according to its functionalities and properties. This paper presents a development of a sensor classification scheme based on the frequency spectrum of the signals and on a statistical metrics. Bearing these ideas in mind, this paper is organized as follows. Section 2 describes briefly the robotic system enhanced with the instrumentation setup. Section 3 presents the experimental results. Finally, section 4 draws the main conclusions and points out future work.
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BACKGROUND: Robot surgery is a further step towards new potential developments in minimally invasive surgery. Surgeons must keep abreast of these new technologies and learn their limits and possibilities. Robot-assisted laparoscopic cholecystectomy has not yet been performed in our institution. The purpose of this report is to present the pathway of implementation of robotic laparoscopic cholecystectomy in a university hospital. METHODS: The Zeus(R) robot system was used. Experimental training was performed on animals. The results of our experimental training allowed us to perform our first two clinical cases. RESULTS: Robot arm set-up and trocar placement required 53 and 35 minutes. Operative time were 59 and 45 minutes respectively. The overall operative time was 112 and 80 minutes, respectively. There were no intraoperative complications. Patients were discharged from the hospital after an overnight stay. CONCLUSION: Robotic laparoscopic cholecystectomy is safe and patient recovery similar to those of standard laparoscopy. At present, there are no advantages of robotic over conventional surgery. Nevertheless, robots have the potential to revolutionise the way surgery is performed. Robot surgery is not reserved for a happy few. This technology deserves more attention because it has the potential to change the way surgery is performed.
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This thesis investigates a method for human-robot interaction (HRI) in order to uphold productivity of industrial robots like minimization of the shortest operation time, while ensuring human safety like collision avoidance. For solving such problems an online motion planning approach for robotic manipulators with HRI has been proposed. The approach is based on model predictive control (MPC) with embedded mixed integer programming. The planning strategies of the robotic manipulators mainly considered in the thesis are directly performed in the workspace for easy obstacle representation. The non-convex optimization problem is approximated by a mixed-integer program (MIP). It is further effectively reformulated such that the number of binary variables and the number of feasible integer solutions are drastically decreased. Safety-relevant regions, which are potentially occupied by the human operators, can be generated online by a proposed method based on hidden Markov models. In contrast to previous approaches, which derive predictions based on probability density functions in the form of single points, such as most likely or expected human positions, the proposed method computes safety-relevant subsets of the workspace as a region which is possibly occupied by the human at future instances of time. The method is further enhanced by combining reachability analysis to increase the prediction accuracy. These safety-relevant regions can subsequently serve as safety constraints when the motion is planned by optimization. This way one arrives at motion plans that are safe, i.e. plans that avoid collision with a probability not less than a predefined threshold. The developed methods have been successfully applied to a developed demonstrator, where an industrial robot works in the same space as a human operator. The task of the industrial robot is to drive its end-effector according to a nominal sequence of grippingmotion-releasing operations while no collision with a human arm occurs.
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The ground-based Atmospheric Radiation Measurement Program (ARM) and NASA Aerosol Robotic Net- work (AERONET) routinely monitor clouds using zenith ra- diances at visible and near-infrared wavelengths. Using the transmittance calculated from such measurements, we have developed a new retrieval method for cloud effective droplet size and conducted extensive tests for non-precipitating liquid water clouds. The underlying principle is to combine a liquid-water-absorbing wavelength (i.e., 1640 nm) with a non-water-absorbing wavelength for acquiring information on cloud droplet size and optical depth. For simulated stratocumulus clouds with liquid water path less than 300 g m−2 and horizontal resolution of 201 m, the retrieval method underestimates the mean effective radius by 0.8μm, with a root-mean-squared error of 1.7 μm and a relative deviation of 13%. For actual observations with a liquid water path less than 450 g m−2 at the ARM Oklahoma site during 2007– 2008, our 1.5-min-averaged retrievals are generally larger by around 1 μm than those from combined ground-based cloud radar and microwave radiometer at a 5-min temporal resolution. We also compared our retrievals to those from combined shortwave flux and microwave observations for relatively homogeneous clouds, showing that the bias between these two retrieval sets is negligible, but the error of 2.6 μm and the relative deviation of 22 % are larger than those found in our simulation case. Finally, the transmittance-based cloud effective droplet radii agree to better than 11 % with satellite observations and have a negative bias of 1 μm. Overall, the retrieval method provides reasonable cloud effective radius estimates, which can enhance the cloud products of both ARM and AERONET.
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This work presents a method of information fusion involving data captured by both a standard CCD camera and a ToF camera to be used in the detection of the proximity between a manipulator robot and a human. Both cameras are assumed to be located above the work area of an industrial robot. The fusion of colour images and time of light information makes it possible to know the 3D localization of objects with respect to a world coordinate system. At the same time this allows to know their colour information. Considering that ToF information given by the range camera contains innacuracies including distance error, border error, and pixel saturation, some corrections over the ToF information are proposed and developed to improve the results. The proposed fusion method uses the calibration parameters of both cameras to reproject 3D ToF points, expressed in a common coordinate system for both cameras and a robot arm, in 2D colour images. In addition to this, using the 3D information, the motion detection in a robot industrial environment is achieved, and the fusion of information is applied to the foreground objects previously detected. This combination of information results in a matrix that links colour and 3D information, giving the possibility of characterising the object by its colour in addition to its 3D localization. Further development of these methods will make it possible to identify objects and their position in the real world, and to use this information to prevent possible collisions between the robot and such objects.
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This work presents a method of information fusion involving data captured by both a standard charge-coupled device (CCD) camera and a time-of-flight (ToF) camera to be used in the detection of the proximity between a manipulator robot and a human. Both cameras are assumed to be located above the work area of an industrial robot. The fusion of colour images and time-of-flight information makes it possible to know the 3D localization of objects with respect to a world coordinate system. At the same time, this allows to know their colour information. Considering that ToF information given by the range camera contains innacuracies including distance error, border error, and pixel saturation, some corrections over the ToF information are proposed and developed to improve the results. The proposed fusion method uses the calibration parameters of both cameras to reproject 3D ToF points, expressed in a common coordinate system for both cameras and a robot arm, in 2D colour images. In addition to this, using the 3D information, the motion detection in a robot industrial environment is achieved, and the fusion of information is applied to the foreground objects previously detected. This combination of information results in a matrix that links colour and 3D information, giving the possibility of characterising the object by its colour in addition to its 3D localisation. Further development of these methods will make it possible to identify objects and their position in the real world and to use this information to prevent possible collisions between the robot and such objects.
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We discussed a floating mechanism based on quasi-magnetic levitation method that can be attached at the endpoint of a robot arm in order to construct a novel redundant robot arm for producing compliant motions. The floating mechanism can be composed of magnets and a constraint mechanism such that the repelling force of the magnets floats the endpoint part of the mechanism stable for the guided motions. The analytical and experimental results show that the proposed floating mechanism can produce stable floating motions with small inertia and viscosity. The results also show that the proposed mechanism can detect small force applied to the endpoint part because the friction force of the mechanism is very small.
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The loss of motor function at the elbow joint can result as a consequence of stroke. Stroke is a clinical illness resulting in long lasting neurological deficits often affecting somatosensory and motor cortices. More than half of those that recover from a stroke survive with disability in their upper arm and need rehabilitation therapy to help in regaining functions of daily living. In this paper, we demonstrated a prototype of a low-cost, ultra-light and wearable soft robotic assistive device that could aid administration of elbow motion therapies to stroke patients. In order to assist the rotation of the elbow joint, the soft modules which consist of soft wedge-like cellular units was inflated by air to produce torque at the elbow joint. Highly compliant rotation can be naturally realised by the elastic property of soft silicone and pneumatic control of air. Based on the direct visual-actuation control, a higher control loop utilised visual processing to apply positional control, the lower control loop was implemented by an electronic circuit to achieve the desired pressure of the soft modules by Pulse Width Modulation. To examine the functionality of the proposed soft modular system, we used an anatomical model of the upper limb and performed the experiments with healthy participants.
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The equations corresponding to Newton-Euler iterative method for the determination of forces and moments acting on the rigid links of a robotic manipulator are given a new treatment using composed vectors for the representation of both kinematical and dynamical quantities. It is shown that Lagrange equations for the motion of a holonomic system are easily found from the composed vectors defined in this note. Application to a simple model of an industrial robot shows that the method developed in these notes is efficient in solving the dynamics of a robotic manipulator. An example is developed, where it is seen that with the application of appropriate control moments applied to each arm of the robot, starting from a given initial position, it is possible to reach equilibrium in a final pre-assigned position.
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In this paper the dynamical interactions of a double pendulum arm and an electromechanical shaker is investigated. The double pendulum is a three degree of freedom system coupled to an RLC circuit based nonlinear shaker through a magnetic field, and the capacitor voltage is a nonlinear function of the instantaneous electric charge. Numerical simulations show the existence of chaotic behavior for some regions in the parameter space and this behaviour is characterized by power spectral density and Lyapunov exponents. The bifurcation diagram is constructed to explore the qualitative behaviour of the system. This kind of electromechanical system is frequently found in robotic systems, and in order to suppress the chaotic motion, the State-Dependent Riccati Equation (SDRE) control and the Nonlinear Saturation control (NSC) techniques are analyzed. The robustness of these two controllers is tested by a sensitivity analysis to parametric uncertainties.
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The application of dexterous robotic hands out of research laboratories has been limited by the intrinsic complexity that these devices present. This is directly reflected as an economically unreasonable cost and a low overall reliability. Within the research reported in this thesis it is shown how the problem of complexity in the design of robotic hands can be tackled, taking advantage of modern technologies (i.e. rapid prototyping), leading to innovative concepts for the design of the mechanical structure, the actuation and sensory systems. The solutions adopted drastically reduce the prototyping and production costs and increase the reliability, reducing the number of parts required and averaging their single reliability factors. In order to get guidelines for the design process, the problem of robotic grasp and manipulation by a dual arm/hand system has been reviewed. In this way, the requirements that should be fulfilled at hardware level to guarantee successful execution of the task has been highlighted. The contribution of this research from the manipulation planning side focuses on the redundancy resolution that arise in the execution of the task in a dexterous arm/hand system. In literature the problem of coordination of arm and hand during manipulation of an object has been widely analyzed in theory but often experimentally demonstrated in simplified robotic setup. Our aim is to cover the lack in the study of this topic and experimentally evaluate it in a complex system as a anthropomorphic arm hand system.