CSI related dynamics and control issues in space robotics

The research addressed includes: (1) CSI issues in space robotics; (2) control of elastic payloads, which includes 1-DOF example, and 3-DOF harmonic drive arm with elastic beam; and (3) control of large space arms with elastic links, which includes testbed description, modeling, and experimental implementation of colocated PD and end-point tip position controllers

Learning Task Constraints from Demonstration for Hybrid Force/Position Control

We present a novel method for learning hybrid force/position control from demonstration. We learn a dynamic constraint frame aligned to the direction of desired force using Cartesian Dynamic Movement Primitives. In contrast to approaches that utilize a fixed constraint frame, our approach easily accommodates tasks with rapidly changing task constraints over time. We activate only one degree of freedom for force control at any given time, ensuring motion is always possible orthogonal to the direction of desired force. Since we utilize demonstrated forces to learn the constraint frame, we are able to compensate for forces not detected by methods that learn only from the demonstrated kinematic motion, such as frictional forces between the end-effector and the contact surface. We additionally propose novel extensions to the Dynamic Movement Primitive (DMP) framework that encourage robust transition from free-space motion to in-contact motion in spite of environment uncertainty. We incorporate force feedback and a dynamically shifting goal to reduce forces applied to the environment and retain stable contact while enabling force control. Our methods exhibit low impact forces on contact and low steady-state tracking error.Comment: Under revie

Investigation of an actively controlled robot arm for vibration suppression in milling

In recent years, the use of robotic systems to enhance the productivity of machining operations has received significant attention from the research and manufacturing communities. Robots have the potential to further improve productivity, for example by providing automated workpiece fixturing, or by providing a flexible and reconfigurable platform from which a variety of subtractive or additive manufacturing operations could be performed. One possible approach is the use of a robotic arm to provide additional fixturing or support of the workpiece during the machining operation. This can increase the stiffness of the workpiece system during machining, which can improve productivity by limiting the onset of undesirable vibrations such as chatter. Chatter is a form of self-excited vibration which leads to low surface quality of the workpiece, shortens the cutting tool life and increases the cutting forces. In this paper, an actively controlled robot arm is simulated in order to suppress the chatter, in an effort to further improve the chatter stability. During the milling operation, preload can be applied through the robot to support the flexible structure, however, the robot cannot suppress high-frequency forces. Since the stiffness and damping ratio of the large flexible structure vary during the operation due to material removal, active vibration control is performed. A proof-mass actuator is proposed that can provide 45 N force up to 2000 Hz with 2 mm stroke. The dynamic properties of the device are identified experimentally as part of a model of a robot fixture prototype. The robotic arm is modelled as a three degree of freedom system; this is combined with a simplified representation of the workpiece dynamics, and the proof-mass actuator, within a Matlab environment. The effect of active control on the chatter stability is evaluated, focussing initially on the use of direct velocity feedback as a control strategy. Estimated chatter stability predictions, along with time, frequency domain simulation results, show that the application of active control method in robotic-assisted machining can suppress the chatter vibrations during machining and hence increase productivity

Shared control for natural motion and safety in hands-on robotic surgery

Hands-on robotic surgery is where the surgeon controls the tool's motion by applying forces and torques to the robot holding the tool, allowing the robot-environment interaction to be felt though the tool itself. To further improve results, shared control strategies are used to combine the strengths of the surgeon with those of the robot. One such strategy is active constraints, which prevent motion into regions deemed unsafe or unnecessary. While research in active constraints on rigid anatomy has been well-established, limited work on dynamic active constraints (DACs) for deformable soft tissue has been performed, particularly on strategies which handle multiple sensing modalities. In addition, attaching the tool to the robot imposes the end effector dynamics onto the surgeon, reducing dexterity and increasing fatigue. Current control policies on these systems only compensate for gravity, ignoring other dynamic effects. This thesis presents several research contributions to shared control in hands-on robotic surgery, which create a more natural motion for the surgeon and expand the usage of DACs to point clouds. A novel null-space based optimization technique has been developed which minimizes the end effector friction, mass, and inertia of redundant robots, creating a more natural motion, one which is closer to the feeling of the tool unattached to the robot. By operating in the null-space, the surgeon is left in full control of the procedure. A novel DACs approach has also been developed, which operates on point clouds. This allows its application to various sensing technologies, such as 3D cameras or CT scans and, therefore, various surgeries. Experimental validation in point-to-point motion trials and a virtual reality ultrasound scenario demonstrate a reduction in work when maneuvering the tool and improvements in accuracy and speed when performing virtual ultrasound scans. Overall, the results suggest that these techniques could increase the ease of use for the surgeon and improve patient safety.Open Acces

Constrained DMPs for Feasible Skill Learning on Humanoid Robots

In the context of humanoid skill learning, movement primitives have gained much attention because of their compact representation and convenient combination with a myriad of optimization approaches. Among them, a well-known scheme is to use Dynamic Movement Primitives (DMPs) with reinforcement learning (RL) algorithms. While various remarkable results have been reported, skill learning with physical constraints has not been sufficiently investigated. For example, when RL is employed to optimize the robot joint trajectories, the exploration noise could drive the resulting trajectory out of the joint limits. In this paper, we focus on robot skill learning characterized by joint limit avoidance, by introducing the novel Constrained Dynamic Movement Primitives (CDMPs). By controlling a set of transformed states (called exogenous states) instead of the original DMPs states, CDMPs are capable of maintaining the joint trajectories within the safety limits. We validate CDMPs on the humanoid robot iCub, showing the applicability of our approach

Robotic manipulation planning for shaping deformable linear objects with environmental contacts

Humans use contacts in the environment to modify the shape of deformable objects. Yet, few papers have studied the use of contacts in robotic manipulation. In this paper, we investigate the problem of robotic manipulation of cables with environmental contacts. Instead of avoiding contacts, we propose a framework that allows the robot to use them for shaping the cable. We introduce an index to quantify the contact mobility of a cable with a circular contact. Based on this index, we present a planner to plan robot motions. The planner is aided by a vision-based contact detector. The framework is validated with robot experiments on different desired cable configurations

Minimising vibration in a flexible golf club during robotic simulations of a golf swing

Robots are widely used as substitutes for humans in situations involving repetitive tasks where a precise and repeatable motion is required. Sports technology is an area which has seen an increase in the implementation of robots which simulate specific human motions required for a sport. One purpose is to test sports equipment, where the requirement is for a motion to be performed with consistent variables. One issue which has arisen frequently in the robot simulation of humans is the inherent presence of vibration excited in a flexible object being manipulated by a robot, and this issue is not unfounded in the situation presented in this research, of a golf robot manipulating a flexible golf club during the simulation of a golf swing. It had been found that during robotic simulations of golf swings performed with the Miyamae Robo V at the Sports Technology Institute at Loughborough University, swing variables such as shaft deformation and clubhead orientation were dissimilar to those measured for human golf swings. Vibrations present in the golf club were identified as the key cause of the disparity between human and robot swing variables. This research sought to address this issue and find a method which could be applied to reduce clubhead vibrations present in robot simulations of a golf swing to improve their similarity to human swings. This would facilitate the use of the golf robot for equipment testing and club fitting. Golf swing variables were studied and measured for 14 human subjects with the aim being to understand the motion that the robot is required to simulate. A vibration damping gripper was then fitted to the robot to test the effect that changing the interface between the robot-excited vibrations and the club would have, this was achieved with a selection of silicone sleeves with differing material properties which could be attached to the club. Preliminary results showed a noticeable reduction in clubhead vibrations and this solution was investigated further. Mathematically modelling the robot was seen as the most suitable method for this as it meant the robot remained functional and allowed a number of solutions to be tested. Several iterations of a mathematical model were developed with the final model being structurally similar to the robot with the addition of a compliant grip and wrist. The method by which the robot is driven was also recognised as having a large effect on the level of vibration excited in the clubhead and the methodology behind generating smooth robot swing profiles is presented. The mathematical model was used to perform 6 swings and the resulting shaft deformation and clubhead vibration were compared with data from human swings. It was found that the model was capable of producing swing variables comparable to human swings, however in the downswing portion of the swing the magnitude of these variables were larger for the simulations. Simulations were made which sought to demonstrate the difference between the model replicating the rigid robot and a compliant system. Reductions in vibration were achieved in all swings, including those driven with robot feedback data which contains oscillations excited by the method with which the robot is driven