Safe Robotic Grasping: Minimum Impact-Force Grasp Selection

This paper addresses the problem of selecting from a choice of possible grasps, so that impact forces will be minimised if a collision occurs while the robot is moving the grasped object along a post-grasp trajectory. Such considerations are important for safety in human-robot interaction, where even a certified "human-safe" (e.g. compliant) arm may become hazardous once it grasps and begins moving an object, which may have significant mass, sharp edges or other dangers. Additionally, minimising collision forces is critical to preserving the longevity of robots which operate in uncertain and hazardous environments, e.g. robots deployed for nuclear decommissioning, where removing a damaged robot from a contaminated zone for repairs may be extremely difficult and costly. Also, unwanted collisions between a robot and critical infrastructure (e.g. pipework) in such high-consequence environments can be disastrous. In this paper, we investigate how the safety of the post-grasp motion can be considered during the pre-grasp approach phase, so that the selected grasp is optimal in terms applying minimum impact forces if a collision occurs during a desired post-grasp manipulation. We build on the methods of augmented robot-object dynamics models and "effective mass" and propose a method for combining these concepts with modern grasp and trajectory planners, to enable the robot to achieve a grasp which maximises the safety of the post-grasp trajectory, by minimising potential collision forces. We demonstrate the effectiveness of our approach through several experiments with both simulated and real robots.Comment: To be appeared in IEEE/RAS IROS 201

Kontextsensitive Körperregulierung für redundante Roboter

In the past few decades the classical 6 degrees of freedom manipulators' dominance has been challenged by the rise of 7 degrees of freedom redundant robots. Similarly, with increased availability of humanoid robots in academic research, roboticists suddenly have access to highly dexterous platforms with multiple kinematic chains capable of undertaking multiple tasks simultaneously. The execution of lower-priority tasks, however, are often done in task/scenario specific fashion. Consequently, these systems are not scalable and slight changes in the application often implies re-engineering the entire control system and deployment which impedes the development process over time. This thesis introduces an alternative systematic method of addressing the secondary tasks and redundancy resolution called, context aware body regulation. Contexts consist of one or multiple tasks, however, unlike the conventional definitions, the tasks within a context are not rigidly defined and maintain some level of abstraction. For instance, following a particular trajectory constitutes a concrete task while performing a Cartesian motion with the end-effector represents an abstraction of the same task and is more appropriate for context formulation. Furthermore, contexts are often made up of multiple abstract tasks that collectively describe a reoccurring situation. Body regulation is an umbrella term for a collection of schemes for addressing the robots' redundancy when a particular context occurs. Context aware body regulation offers several advantages over traditional methods. Most notably among them are reusability, scalability and composability of contexts and body regulation schemes. These three fundamental concerns are realized theoretically by in-depth study and through mathematical analysis of contexts and regulation strategies; and are practically implemented by a component based software architecture that complements the theoretical aspects. The findings of the thesis are applicable to any redundant manipulator and humanoids, and allow them to be used in real world applications. Proposed methodology presents an alternative approach for the control of robots and offers a new perspective for future deployment of robotic solutions.Im Verlauf der letzten Jahrzehnte wich der Einfluss klassischer Roboterarme mit 6 Freiheitsgraden zunehmend denen neuer und vielfältigerer Manipulatoren mit 7 Gelenken. Ebenso stehen der Forschung mit den neuartigen Humanoiden inzwischen auch hoch-redundante Roboterplattformen mit mehreren kinematischen Ketten zur Verfügung. Diese überaus flexiblen und komplexen Roboter-Kinematiken ermöglichen generell das gleichzeitige Verfolgen mehrerer priorisierter Bewegungsaufgaben. Die Steuerung der weniger wichtigen Aufgaben erfolgt jedoch oft in anwendungsspezifischer Art und Weise, welche die Skalierung der Regelung zu generellen Kontexten verhindert. Selbst kleine Änderungen in der Anwendung bewirken oft schon, dass große Teile der Robotersteuerung überarbeitet werden müssen, was wiederum den gesamten Entwicklungsprozess behindert. Diese Dissertation stellt eine alternative, systematische Methode vor um die Redundanz neuer komplexer Robotersysteme zu bewältigen und vielfältige, priorisierte Bewegungsaufgaben parallel zu steuern: Die so genannte kontextsensitive Körperregulierung. Darin bestehen Kontexte aus einer oder mehreren Bewegungsaufgaben. Anders als in konventionellen Anwendungen sind die Aufgaben nicht fest definiert und beinhalten eine gewisse Abstraktion. Beispielsweise stellt das Folgen einer bestimmten Trajektorie eine sehr konkrete Bewegungsaufgabe dar, während die Ausführung einer Kartesischen Bewegung mit dem Endeffektor eine Abstraktion darstellt, die für die Kontextformulierung besser geeignet ist. Kontexte setzen sich oft aus mehreren solcher abstrakten Aufgaben zusammen und beschreiben kollektiv eine sich wiederholende Situation. Durch die Verwendung der kontextsensitiven Körperregulierung ergeben sich vielfältige Vorteile gegenüber traditionellen Methoden: Wiederverwendbarkeit, Skalierbarkeit, sowie Komponierbarkeit von Konzepten. Diese drei fundamentalen Eigenschaften werden in der vorliegenden Arbeit theoretisch mittels gründlicher mathematischer Analyse aufgezeigt und praktisch mittels einer auf Komponenten basierenden Softwarearchitektur realisiert. Die Ergebnisse dieser Dissertation lassen sich auf beliebige redundante Manipulatoren oder humanoide Roboter anwenden und befähigen diese damit zur realen Anwendung außerhalb des Labors. Die hier vorgestellte Methode zur Regelung von Robotern stellt damit eine neue Perspektive für die zukünftige Entwicklung von robotischen Lösungen dar

Self-motion control of kinematically redundant robot manipulators

Thesis (Master)--Izmir Institute of Technology, Mechanical Engineering, Izmir, 2012Includes bibliographical references (leaves: 88-92)Text in English; Abstract: Turkish and Englishxvi,92 leavesRedundancy in general provides space for optimization in robotics. Redundancy can be defined as sensor/actuator redundancy or kinematic redundancy. The redundancy considered in this thesis is the kinematic redundancy where the total degrees-of-freedom of the robot is more than the total degrees-of-freedom required for the task to be executed. This provides infinite number of solutions to perform the same task, thus, various subtasks can be carried out during the main-task execution. This work utilizes the property of self-motion for kinematically redundant robot manipulators by designing the general subtask controller that controls the joint motion in the null-space of the Jacobian matrix. The general subtask controller is implemented for various subtasks in this thesis. Minimizing the total joint motion, singularity avoidance, posture optimization for static impact force objectives, which include maximizing/minimizing the static impact force magnitude, and static and moving obstacle (point to point) collision avoidance are the subtasks considered in this thesis. New control architecture is developed to accomplish both the main-task and the previously mentioned subtasks. In this architecture, objective function for each subtask is formed. Then, the gradient of the objective function is used in the subtask controller to execute subtask objective while tracking a given end-effector trajectory. The tracking of the end-effector is called main-task. The SCHUNK LWA4-Arm robot arm with seven degrees-of-freedom is developed first in SolidWorks® as a computer-aided-design (CAD) model. Then, the CAD model is converted to MATLAB® Simulink model using SimMechanics CAD translator to be used in the simulation tests of the controller. Kinematics and dynamics equations of the robot are derived to be used in the controllers. Simulation test results are presented for the kinematically redundant robot manipulator operating in 3D space carrying out the main-task and the selected subtasks for this study. The simulation test results indicate that the developed controller’s performance is successful for all the main-task and subtask objectives

Robust Grasp with Compliant Multi-Fingered Hand

As robots find more and more applications in unstructured environments, the need for grippers able to grasp and manipulate a large variety of objects has brought consistent attention to the use of multi-fingered hands. The hardware development and the control of these devices have become one of the most active research subjects in the field of grasping and dexterous manipulation. Despite a large number of publications on grasp planning, grasping frameworks that strongly depend on information collected by touching the object are getting attention only in recent years. The objective of this thesis focuses on the development of a controller for a robotic system composed of a 7-dof collaborative arm + a 16-dof torque-controlled multi-fingered hand to successfully and robustly grasp various objects. The robustness of the grasp is increased through active interaction between the object and the arm/hand robotic system. Algorithms that rely on the kinematic model of the arm/hand system and its compliance characteristics are proposed and tested on real grasping applications. The obtained results underline the importance of taking advantage of information from hand-object contacts, which is necessary to achieve human-like abilities in grasping tasks

Null-Space Minimization of Center of Gravity Displacementof a Redundant Aerial Manipulator

Displacements of the base during trajectory tracking are a common issue in the control of aerial manipulators. These are caused by reaction torques transferred to the base due to the manipulator motion and, in particular, to the motion of its center of gravity. We present a novel approach to reduce base displacements of a kinematically redundant aerial manipulator by using null-space projection in the inverse kinematic control. A secondary objective function minimizes the horizontal displacement of the manipulator center of gravity. We test this algorithm on different trajectories for both three and four degrees of freedom (DOF) manipulators in a simulation environment. The results comparing our algorithm with inverse kinematic control without the null-space projection show up to an 80% reduction in the end-effector position error and an average of about 56% reduction in maximum base displacement. The simulation implementation also runs faster than in real-time in our code implementation. We provide a workspace analysis based on multiple stopping criteria such as excessive base displacement, joint velocities and end-effector position error for the 3 and 4 DOF manipulators. As expected, the 4 DOF manipulator has a larger workspace

Kinematic functions for redundancy resolution using configuration control

The invention fulfills new goals for redundancy resolution based on manipulator dynamics and end-effector characteristics. These goals are accomplished by employing the recently developed configuration control approach. Redundancy resolution is achieved by controlling the joint inertia matrix of the end-effector mass matrix that affect the inertial torques or by reducing the joint torques due to gravity loading and payload. The manipulator mechanical-advantage and velocity-ratio are also used as performance measures to be improved by proper utilization of redundancy. Furthermore, end-effector compliance, sensitivity, and impulsive force at impact are introduced as redundancy resolution criteria. The new goals for redundancy resolution allow a more efficient utilization of the redundant joints based on the desired task requirements

Task-Space Control of Articulated Mobile Robots With a Soft Gripper for Operations

A task-space method is presented for the control of a head-raising articulated mobile robot, allowing the trajectory tracking of a tip of a gripper located on the head of the robot in various operations, e.g., picking up an object and rotating a valve. If the robot cannot continue moving because it reaches a joint angle limit, the robot moves away from the joint limit and changes posture by switching the allocation of lifted/grounded wheels. An articulated mobile robot with a gripper that can grasp objects using jamming transition was developed, and experiments were conducted to demonstrate the effectiveness of the proposed controller in operations

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