181 research outputs found

    The design and control of an actively restrained passive mechatronic system for safety-critical applications

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    Development of manipulators that interact closely with humans has been a focus of research in fields such as robot-assisted surgery and haptic interfaces for many years. Recent introduction of powered surgical-assistant devices into the operating theatre has meant that robot manipulators have been required to interact with both patients and surgeons. Most of these manipulators are modified industrial robots. However, the use of high-powered mechanisms in the operating theatre could compromise safety of the patient, surgeon, and operating room staff. As a solution to the safety problem, the use of actively restrained passive arms has been proposed. Clutches or brakes at each joint are used to restrict the motion of the end-effector to restrain it to a pre-defined region or path. However, these devices have only had limited success in following pre-defined paths under human guidance. In this research, three major limitations of existing passive devices actively restrained are addressed. [Continues.

    Understanding and Improving Locomotion: The Simultaneous Optimization of Motion and Morphology in Legged Robots

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    There exist many open design questions in the field of legged robotics. Should leg extension and retraction occur with a knee or a prismatic joint? Will adding a compliant ankle lead to improved energetics compared to a point foot? Should quadrupeds have a flexible or a rigid spine? Should elastic elements in the actuation be placed in parallel or in series with the motors? Though these questions may seem basic, they are fundamentally difficult to approach. A robot with either discrete choice will likely need very different components and use very different motion to perform at its best. To make a fair comparison between two design variations, roboticists need to ask, is the best version of a robot with a discrete morphological variation better than the best version of a robot with the other variation? In this dissertation, I propose to answer these type of questions using an optimization based approach. Using numerical algorithms, I let a computer determine the best possible motion and best set of parameters for each design variation in order to be able to compare the best instance of each variation against each other. I developed and implemented that methodology to explore three primary robotic design questions. In the first, I asked if parallel or series elastic actuation is the more energetically economical choice for a legged robot. Looking at a variety of force and energy based cost functions, I mapped the optimal motion cost landscape as a function of configurable parameters in the hoppers. In the best case, the series configuration was more economical for an energy based cost function, and the parallel configuration was better for a force based cost function. I then took this work a step further and included the configurable parameters directly within the optimization on a model with gear friction. I found, for the most realistic cost function, the electrical work, that series was the better choice when the majority of the transmission was handled by a low-friction rotary-to-linear transmission. In the second design question, I extended this analysis to a two-dimensional monoped moving at a forward velocity with either parallel or series elastic actuation at the hip and leg. In general it was best to have a parallel elastic actuator at the hip, and a series elastic actuator at the leg. In the third design question, I asked if there is an energetic benefit to having an articulated spinal joint instead of a rigid spinal joint in a quadrupedal legged robot. I found that the answer was gait dependent. For symmetrical gaits, such as walking and trotting, the rigid and articulated spine models have similar energetic economy. For asymmetrical gaits, such as bounding and galloping, the articulated spine led to significant energy savings at high speeds. The combination of the above studies readily presents a methodology for simultaneously optimizing for motion and morphology in legged robots. Aside from giving insight into these specific design questions, the technique can also be extended to a variety of other design questions. The explorations in turn inform future hardware development by roboticists and help explain why animals in nature move in the ways that they do.PHDMechanical EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttps://deepblue.lib.umich.edu/bitstream/2027.42/144074/1/yevyes_1.pd

    Adaptive robust interaction control for low-cost robotic grasping

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    Robotic grasping is a challenging area in the field of robotics. When a gripper starts interacting with an object to perform a grasp, the mechanical properties of the object (stiffness and damping) will play an important role. A gripper which is stable in isolated conditions, can become unstable when coupled to an object. This can lead to the extreme condition where the gripper becomes unstable and generates excessive or insufficient grip force resulting in the grasped object either being crushed, or falling and breaking. In addition to the stability issue, grasp maintenance is one of the most important requirements of any grasp where it guarantees a secure grasp in the presence of any unknown disturbance. The term grasp maintenance refers to the reaction of the controller in the presence of external disturbances, trying to prevent any undesired slippage. To do so, the controller continuously adjusts the grip force. This is a challenging task as it requires an accurate model of the friction and object’s weight to estimate a sufficient grip force to stop the object from slipping while incurring minimum deformation. Unfortunately, in reality, there is no solution which is able to obtain the mechanical properties, frictional coefficient and weight of an object before establishing a mechanical interaction with it. External disturbance forces are also stochastic meaning they are impossible to predict. This thesis addresses both of the problems mentioned above by:Creating a novel variable stiffness gripper, capable of grasping unknown objects, mainly those found in agricultural or food manufacturing companies. In addition to the stabilisation effect of the introduced variable stiffness mechanism, a novel force control algorithm has been designed that passively controls the grip force in variable stiffness grippers. Due to the passive nature of the suggested controller, it completely eliminates the necessity for any force sensor. The combination of both the proposed variable stiffness gripper and the passivity based control provides a unique solution for the stable grasp and force control problem in tendon driven, angular grippers.Introducing a novel active multi input-multi output slip prevention algorithm. The algorithm developed provides a robust control solution to endow direct drive parallel jaw grippers with the capability to stop held objects from slipping while incurring minimum deformation; this can be done without any prior knowledge of the object’s friction and weight. The large number of experiments provided in this thesis demonstrate the robustness of the proposed controller when controlling parallel jaw grippers in order to quickly grip, lift and place a broad range of objects firmly without dropping or crushing them. This is particularly useful for teleoperation and nuclear decommissioning tasks where there is often no accurate information available about the objects to be handled. This can mean that pre-programming of the gripper is required for each different object and for high numbers of objects this is impractical and overly time-consuming. A robust controller, which is able to compensate for any uncertainties regarding the object model and any unknown external disturbances during grasping, is implemented. This work has advanced the state of the art in the following two main areas: Direct impedance modulation for stable grasping in tendon driven, angular grippers. Active MIMO slip prevention grasp control for direct drive parallel jaw grippers
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