67 research outputs found

    Experiences with the JPL telerobot testbed: Issues and insights

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    The Jet Propulsion Laboratory's (JPL) Telerobot Testbed is an integrated robotic testbed used to develop, implement, and evaluate the performance of advanced concepts in autonomous, tele-autonomous, and tele-operated control of robotic manipulators. Using the Telerobot Testbed, researchers demonstrated several of the capabilities and technological advances in the control and integration of robotic systems which have been under development at JPL for several years. In particular, the Telerobot Testbed was recently employed to perform a near completely automated, end-to-end, satellite grapple and repair sequence. The task of integrating existing as well as new concepts in robot control into the Telerobot Testbed has been a very difficult and timely one. Now that researchers have completed the first major milestone (i.e., the end-to-end demonstration) it is important to reflect back upon experiences and to collect the knowledge that has been gained so that improvements can be made to the existing system. It is also believed that the experiences are of value to the others in the robotics community. Therefore, the primary objective here will be to use the Telerobot Testbed as a case study to identify real problems and technological gaps which exist in the areas of robotics and in particular systems integration. Such problems have surely hindered the development of what could be reasonably called an intelligent robot. In addition to identifying such problems, researchers briefly discuss what approaches have been taken to resolve them or, in several cases, to circumvent them until better approaches can be developed

    On learning task-directed motion plans

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    Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2009.Includes bibliographical references (p. 119-129).Robotic motion planning is a hard problem for robots with more than just a few degrees of freedom. Modern probabilistic planners are able to solve many problems very quickly, but for difficult problems, they are still unacceptably slow for many applications. This thesis concerns the use of previous planning experience to allow the agent to generate motion plans very quickly when faced with new but related problems. We first investigate a technique for learning from previous experience by simply remembering past solutions and applying them where relevant to new problems. We find that this approach is useful in environments with very low variability in obstacle placement and task endpoints, and that it is important to keep the set of stored plans small to improve performance. However, we would like to be able to better generalize our previous experience so we next investigate a technique for learning parameterized motion plans. A parameterized motion plan is a function from planning problem parameters to a motion plan. In our approach, we learn a set of parameterized subpaths, which we can use as suggestions for a probabilistic planner, leading to substantially reduced planning times. We find that this technique is successful in several standard motion planning domains. However, as the domains get more complex, the technique produces less of an advantage. We discover that the learning problem as we have posed it is likely to be intractible, and that the complexity of the problem is due to the redundancy of the robotics platform. We suggest several possible approaches for addressing this problem as future work.by Sarah J. Finney.Ph.D

    Multi-point static dexterous posture manipulation for the stiffness identification of serial kinematic end-effectors.

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    Masters Degree. University of KwaZulu-Natal, Durban.The low stiffness inherent in serial robots hinders its application to perform advanced operations due to its reduced accuracy imparted through deformations within the links and joints. The high repeatability, extended workspace, and speed of serial manipulators make them appealing to perform precision operations as opposed to its alternative, the CNC machine. However, due to the serial arrangement of the linkages of the system, they lack the accuracy to meet present-day demands. To address the low stiffness problem, this research provided a low-cost dexterous posture identification method. The study investigated the joint stiffness of a Fanuc M10-iA 6 Degree of Freedom (DOF) serial manipulator. The investigation involved a multivariable analysis that focused on the robot’s workspace, kinematic singularity, and dexterity to locate high stiffness areas and postures. The joint stiffness modelling applied the Virtual Joint Method (VJM), which replaced the complicated mechanical robot joints with one-dimensional (1-D) springs. The effects of stress and deflection are linearly related; the highest stress in a robot’s structure is distributed to the higher load-bearing elements such as the robot joints, end-effector, and tool. Therefore, by locating optimal postures, the induced stresses can be better regulated throughout the robot’s structure, thereby reducing resonant vibrations of the system and improving process accuracy and repeatability. These aspects are quantifiably pitched in terms of the magnitude differences in the end-effector deflection. The unique combination of the dexterity and the stiffness analyses aimed to provide roboticists and manufacturers with an easy and systematic solution to improve the stiffness, accuracy, and repeatability of their serial robots. A simple, user-friendly and cost-effective alternative to deflection measurements using accelerometers is provided, which offers an alternative to laser tracking devices that are commonly used for studies of this nature. The first investigation focused on identifying the overall workspace of the Fanuc M-10iA robot. The reachable workspace was investigated to understand the functionality and potential of the Fanuc robot. Most robotic studies stem from analysing the workspace since the workspace is a governing factor of the manipulator and end-effector placement, and its operations, in a manufacturing setting. The second investigation looked at identifying non-reachable areas and points surrounding the robot. This analysis, along with the workspace examination, provided a conclusive testing platform to test the dexterity and stiffness methodologies. Although the research focused on fixing the end-effector at a point (static case), the testing platform was structured precisely to cater for all robotic manufacturing tasks that are subjected to high applied forces and vibrations. Such tasks include, but are not limited to, drilling, tapping, fastening, or welding, and some dynamic and hybrid manufacturing operations. The third investigation was the application of a dexterous study that applied an Inverse Kinematic (IK) method to localise multiple robot configurations about a user-defined point in space. This process was necessary since the study is based on a multi-point dexterous posture identification technique to improve the stiffness of Serial Kinematic Machines (SKMs). The stiffness at various points and configurations were tested, which provided a series of stiff and non-stiff areas and postures within the robot’s workspace. MATLAB®, a technical computing software, was used to model the workspace and singularity of the robot. The dexterity and stiffness analyses were numerically evaluated using Wolfram Mathematica. The multivariable analyses served to improve the accuracy of serial robots and promote their functionality towards high force application manufacturing tasks. Apart from the improved stiffness performance offered, the future benefit of the method could advance the longevity of the robot as well as minimise the regular robot maintenance that is often required due to excessive loading, stress, and strain on the robot motors, joints, and links

    Method and apparatus for configuration control of redundant robots

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    A method and apparatus to control a robot or manipulator configuration over the entire motion based on augmentation of the manipulator forward kinematics is disclosed. A set of kinematic functions is defined in Cartesian or joint space to reflect the desirable configuration that will be achieved in addition to the specified end-effector motion. The user-defined kinematic functions and the end-effector Cartesian coordinates are combined to form a set of task-related configuration variables as generalized coordinates for the manipulator. A task-based adaptive scheme is then utilized to directly control the configuration variables so as to achieve tracking of some desired reference trajectories throughout the robot motion. This accomplishes the basic task of desired end-effector motion, while utilizing the redundancy to achieve any additional task through the desired time variation of the kinematic functions. The present invention can also be used for optimization of any kinematic objective function, or for satisfaction of a set of kinematic inequality constraints, as in an obstacle avoidance problem. In contrast to pseudoinverse-based methods, the configuration control scheme ensures cyclic motion of the manipulator, which is an essential requirement for repetitive operations. The control law is simple and computationally very fast, and does not require either the complex manipulator dynamic model or the complicated inverse kinematic transformation. The configuration control scheme can alternatively be implemented in joint space

    Control of Magnetic Continuum Robots for Endoscopy

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    The present thesis discusses the problem of magnetic actuation and control applied to millimetre-scale robots for endoluminal procedures. Magnetic actuation, given its remote manipulation capabilities, has the potential to overcome several limitations of current endoluminal procedures, such as the relatively large size, high sti�ness and limited dexterity of existing tools. The application of functional forces remotely facilitates the development of softer and more dexterous endoscopes, which can navigate with reduced discomfort for the patient. However, the solutions presented in literature are not always able to guarantee smooth navigation in complex and convoluted anatomical structures. This thesis aims at improving the navigational capabilities of magnetic endoluminal robots, towards achieving full autonomy. This is realized by introducing novel design, sensing and control approaches for magnetically actuated soft endoscopes and catheters. First, the application of accurate closed-loop control to a 1 Internal Permanent Magnet (IPM) endoscope was analysed. The proposed approach can guarantee better navigation capabilities, thanks to the manipulation of every mechanical Degree of Freedom (DOF) - 5 DOFs. Speci�cally, it was demonstrated that gravity can be balanced with su�cient accuracy to guarantee tip levitation. In this way contact is minimized and obstacle avoidance improved. Consequently, the overall navigation capabilities of the endoscope were enhanced for given application. To improve exploration of convoluted anatomical pathways, the design of magnetic endoscopes with multiple magnetic elements along their length was introduced. This approach to endoluminal device design can ideally allow manipulation along the full length; facilitating full shape manipulation, as compared to tip-only control. To facilitate the control of multiple magneto-mechanical DOFs along the catheters' length, a magnetic actuation method was developed based on the collaborative robotic manipulation of 2 External Permanent Magnets (EPMs). This method, compared to the state-of-the-art, facilitates large workspace and applied �eld, while guaranteeing dexterous actuation. Using this approach, it was demonstrated that it is possible to actuate up to 8 independent magnetic DOFs. In the present thesis, two di�erent applications are discussed and evaluated, namely: colonoscopy and navigational bronchoscopy. In the former, a single-IPM endoscopic approach is utilized. In this case, the anatomy is large enough to permit equipping the endoscope with a camera; allowing navigation by direct vision. Navigational bronchoscopy, on-the-other-hand, is performed in very narrow peripheral lumina, and navigation is informed via pre-operative imaging. The presented work demonstrates how the design of the magnetic catheters, informed by a pre-operative Computed Tomography (CT) scan, can mitigate the need for intra-operative imaging and, consequently, reduce radiation exposure for patients and healthcare workers. Speci�cally, an optimization routine to design the catheters is presented, with the aim of achieving follow-the-leader navigation without supervision. In both scenarios, analysis of how magnetic endoluminal devices can improve the current practice and revolutionize the future of medical diagnostics and treatment is presented and discussed

    Task-space dynamic control of underwater robots

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    This thesis is concerned with the control aspects for underwater tasks performed by marine robots. The mathematical models of an underwater vehicle and an underwater vehicle with an onboard manipulator are discussed together with their associated properties. The task-space regulation problem for an underwater vehicle is addressed where the desired target is commonly specified as a point. A new control technique is proposed where the multiple targets are defined as sub-regions. A fuzzy technique is used to handle these multiple sub-region criteria effectively. Due to the unknown gravitational and buoyancy forces, an adaptive term is adopted in the proposed controller. An extension to a region boundary-based control law is then proposed for an underwater vehicle to illustrate the flexibility of the region reaching concept. In this novel controller, a desired target is defined as a boundary instead of a point or region. For a mapping of the uncertain restoring forces, a least-squares estimation algorithm and the inverse Jacobian matrix are utilised in the adaptive control law. To realise a new tracking control concept for a kinematically redundant robot, subregion tracking control schemes with a sub-tasks objective are developed for a UVMS. In this concept, the desired objective is specified as a moving sub-region instead of a trajectory. In addition, due to the system being kinematically redundant, the controller also enables the use of self-motion of the system to perform sub-tasks (drag minimisation, obstacle avoidance, manipulability and avoidance of mechanical joint limits)

    Development and evaluation of mixed reality-enhanced robotic systems for intuitive tele-manipulation and telemanufacturing tasks in hazardous conditions

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    In recent years, with the rapid development of space exploration, deep-sea discovery, nuclear rehabilitation and management, and robotic-assisted medical devices, there is an urgent need for humans to interactively control robotic systems to perform increasingly precise remote operations. The value of medical telerobotic applications during the recent coronavirus pandemic has also been demonstrated and will grow in the future. This thesis investigates novel approaches to the development and evaluation of a mixed reality-enhanced telerobotic platform for intuitive remote teleoperation applications in dangerous and difficult working conditions, such as contaminated sites and undersea or extreme welding scenarios. This research aims to remove human workers from the harmful working environments by equipping complex robotic systems with human intelligence and command/control via intuitive and natural human-robot- interaction, including the implementation of MR techniques to improve the user's situational awareness, depth perception, and spatial cognition, which are fundamental to effective and efficient teleoperation. The proposed robotic mobile manipulation platform consists of a UR5 industrial manipulator, 3D-printed parallel gripper, and customized mobile base, which is envisaged to be controlled by non-skilled operators who are physically separated from the robot working space through an MR-based vision/motion mapping approach. The platform development process involved CAD/CAE/CAM and rapid prototyping techniques, such as 3D printing and laser cutting. Robot Operating System (ROS) and Unity 3D are employed in the developing process to enable the embedded system to intuitively control the robotic system and ensure the implementation of immersive and natural human-robot interactive teleoperation. This research presents an integrated motion/vision retargeting scheme based on a mixed reality subspace approach for intuitive and immersive telemanipulation. An imitation-based velocity- centric motion mapping is implemented via the MR subspace to accurately track operator hand movements for robot motion control, and enables spatial velocity-based control of the robot tool center point (TCP). The proposed system allows precise manipulation of end-effector position and orientation to readily adjust the corresponding velocity of maneuvering. A mixed reality-based multi-view merging framework for immersive and intuitive telemanipulation of a complex mobile manipulator with integrated 3D/2D vision is presented. The proposed 3D immersive telerobotic schemes provide the users with depth perception through the merging of multiple 3D/2D views of the remote environment via MR subspace. The mobile manipulator platform can be effectively controlled by non-skilled operators who are physically separated from the robot working space through a velocity-based imitative motion mapping approach. Finally, this thesis presents an integrated mixed reality and haptic feedback scheme for intuitive and immersive teleoperation of robotic welding systems. By incorporating MR technology, the user is fully immersed in a virtual operating space augmented by real-time visual feedback from the robot working space. The proposed mixed reality virtual fixture integration approach implements hybrid haptic constraints to guide the operator’s hand movements following the conical guidance to effectively align the welding torch for welding and constrain the welding operation within a collision-free area. Overall, this thesis presents a complete tele-robotic application space technology using mixed reality and immersive elements to effectively translate the operator into the robot’s space in an intuitive and natural manner. The results are thus a step forward in cost-effective and computationally effective human-robot interaction research and technologies. The system presented is readily extensible to a range of potential applications beyond the robotic tele- welding and tele-manipulation tasks used to demonstrate, optimise, and prove the concepts
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