Comparatively slow growth in energy density of both power storage and generation technologies has placed added emphasis on the need for energy-efficient designs in legged robots. This paper explores the potential of parallel springs in robot limb design. We start by adding what we call the exhaustive parallel compliance matrix (EPCM) to the design. The EPCM is a set of parallel springs, which includes a parallel spring for each joint and a multijoint parallel spring for all possible combinations of the robot's joints. Then, we carefully formulate and compare two performance metrics, which improve various aspects of the system performance. Each performance metric is analyzed and compared, their strengths and weaknesses being rigorously presented. The performance benefits associated with this approach are dramatic. Implementing the spring matrix reduces the sum of square power (SSP) exerted by the actuators by up to 47%, the peak power requirement by almost 40%, the sum of squared current by 55%, and the peak current by 55%. These results were generated using a planar robot limb and a gait trajectory borrowed from biology. We use a fully dynamic model of the robotic system including inertial effects. We also test the design robustness using a perturbation study, which shows that the parallel springs are effective even in the presence of trajectory perturbation.
Comparatively slow growth in power storage and generation makes power-efficient designs desirable for legged robot systems. One important cause of power losses in robotic systems is the mechanical antagonism phenomenon, i.e. one or more motors being used as brakes while the others exert positive energy. This two-part paper first develops a rigorous understanding of mechanical antagonism in multiactuator robotic limbs. We show that, for a 6-DoF robot arm, there exist 4096 distinct regions in the force-velocity space of the end effector (the regions are distinguishable by the sign of the actuator powers). Only sixty-four of these regions correspond with operating points where all actuators exert positive power into the system. In the second part of the paper, we formulate a convex optimization problem which minimizes mechanical antagonism in redundant manipulators. We solve the optimization problem which becomes the derivation for a new, power-optimal, pseudoinverse for non-square Jacobians. In fact, two such pseudoinverses are derived: one for statically determinate systems, such as serial manipulators, and one for statically indeterminate systems, such as parallel manipulators.
The development of control strategies that allow stiff industrial robots to operate safely in unstructured environments is a significant challenge. This paper integrates two strategies that improve safety for industrial manipulators in uncertain conditions. First, software compliance in the task space is implemented using force feedback. End-effector compliance is vital for many tasks, such as interacting with humans or manipulating uncertain payloads. Beyond compliance, a collision detection algorithm detects collisions based on joint torque deviation from a dynamic model. Collisions can be detected at any point along the manipulator via loading or impulse anomalies. Joint torque data is typically noisy, and the accuracy of the robot dynamic model is limited, so an Extended Kalman Filter (EKF) was developed to improve the torque estimates. Experiments and demonstrations were performed using a commercially available 7DOF industrial robot. The EKF improved collision detection during unplanned contact tasks, and the method described here is hardware agnostic and extensible.
Joint torque feedback is useful in serial manipulator control algorithms for contact control, collision detection, performance analysis, etc. For example, the predicted torque can be compared to the measured torque so the system can respond to unexpected or unmodeled physical inputs. The input current to the joint motors can be used to estimate the input torque if the motor parameters are well-understood. However, in a closed commercial system, the motor parameters are often proprietary or unknown. Also, systems that sense or estimate motor torques instead of the joint torques require compensation for gear train losses. In this work, we propose a method for mapping the measured motor current to the joint torque on a serial manipulator without joint torque sensors, thus advancing the potential to implement torque feedback algorithms such as collision detection on any industrial robot with joint position and motor current feedback. This new torque estimating technique (as opposed to using Newton-Euler dynamics) allows for sensing of external forces in collision detection applications for a position controlled robot. The method requires knowledge of the robot link centers of mass, masses, and inertias and that the motor currents and joint positions can be measured. The joint torques due to gravity, inertia, and Coriolis are estimated by the Newton-Euler method using the system geometry, link masses, and the measured joint positions. A method for estimating friction losses using only the current and the predicted joint torque is demonstrated. The measured current, less estimated friction, is then mapped to the joint torque. The validity of the black box joint torque estimating model was demonstrated using two Motoman SIA-5D manipulators with a 3rd party controller provided by Agile Planet. The joints of the robot were moved through a variety of test motions with known joint torque characteristics (as calculated using Newton-Euler dynamics). Estimated joint torques are similar to the calculated torque. Physical significance of the torque is validated by comparing the estimated torque to the calculated torque generated by a known force. The feasibility of the estimated torque error to force detection is discussed in terms of improving the safety and deployment options for industrial robotic systems.
Control of prosthetic devices should be robust and intuitive. In this work a simple, robust, and intuitive method for opening and closing a prosthetic hand for transradial amputations is proposed. The method utilizes force sensitive resistors (FSR) in a sleeve around the residual forearm. Contracting the muscles to open or close the hand changes the shape of the forearm and the force on the FSR sensors. A novel Wheatstone bridge configuration of the sensors simplifies and expediates the calibration. Using all four FSRs as the resistors of the Wheatstone bridge, the system is relatively insensitive to sensor location. To calibrate the sensor, the user opens and closes the hand a few times. The method was demonstrated in simulation on two unamputated individuals opening and closing the hand. To demonstrate the robustness of the method, the sleeve was removed and replaced so that the FSR locations and the calibration is different, but the system is still functional.
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