Geometry-aware Manipulability Learning, Tracking and Transfer

Body posture influences human and robots performance in manipulation tasks, as appropriate poses facilitate motion or force exertion along different axes. In robotics, manipulability ellipsoids arise as a powerful descriptor to analyze, control and design the robot dexterity as a function of the articulatory joint configuration. This descriptor can be designed according to different task requirements, such as tracking a desired position or apply a specific force. In this context, this paper presents a novel \emph{manipulability transfer} framework, a method that allows robots to learn and reproduce manipulability ellipsoids from expert demonstrations. The proposed learning scheme is built on a tensor-based formulation of a Gaussian mixture model that takes into account that manipulability ellipsoids lie on the manifold of symmetric positive definite matrices. Learning is coupled with a geometry-aware tracking controller allowing robots to follow a desired profile of manipulability ellipsoids. Extensive evaluations in simulation with redundant manipulators, a robotic hand and humanoids agents, as well as an experiment with two real dual-arm systems validate the feasibility of the approach.Comment: Accepted for publication in the Intl. Journal of Robotics Research (IJRR). Website: https://sites.google.com/view/manipulability. Code: https://github.com/NoemieJaquier/Manipulability. 24 pages, 20 figures, 3 tables, 4 appendice

Posture-Dependent Projection-Based Force Reflection Algorithms for Bilateral Teleoperators

It was previously established that the projection-based force reflection (PBFR) algorithms improve the overall stability of a force reflecting teleoperation system. The idea behind the PBFR algorithms is to identify the component of the reflected force which is compensated by interaction with the operator\u27s hand, and subsequently attenuate the residual component of the reflected force. If there is no a priori information regarding the behaviour of the human operator, the PBFR gain is selected equal to sufficiently small constant in order to guarantee stability for a wide range of human operator responses. Small PBRF gains, however, may deteriorate the transparency of a teleoperator system. In this thesis, a new method for selecting the PBFR gain is introduced which depends on human postures. Using an online human posture estimation, the introduced posture-dependent PBFR algorithm has been applied to a teleoperation system with force feedback. It is experimentally demonstrated that the developed method for selection of the PBFR gain based on human postures improves the transparency of the teleoperator system while the stability is preserved. Finally, preliminary results that deal with an extension of the developed methods towards a more realistic model of the human arm with 4 degrees of freedom and three dimensional movements are presented

Kinematic study of flight telerobotic servicer configuration issues

Several factors, such as body size and shape, and the number of arms and their placement, will influence how well the Flight Telerobotic Servicer (FTS) is suited to its potential duties for the Space Station Program. In order to examine the implications of these configuration options, eight specific 2, 3, and 4 armed FTS configuration were simulated and used to perform a Space Station Orbital Replacement Unit (ORU) exchange. The strengths and weaknesses of each configuration were evaluated. Although most of the configurations examined were able to perform the exchange, several of the 3 and 4 arm configurations had operational advantages. The results obtained form these simulations are specific to the assumptions associated with the ORU exchange scenario examined. However, they do illustrate the general interrelationships and sensitivities which need to be understood

From handcrafting to a certified and ergonomic collaborative workstation: the digital transformation process

As manufacturing enters an era of mass customization, new technological solutions with more versatility and flexibility are brought to the industry. Collaborative robots, or COBOTs, can now safely work near humans, a key advantage that enables highly-flexible production and opens the possibility to tackle the incidence of occupational health problems. Although the advantages of collaborative robotic manufacturing have been extensively praised, adapting a manual production workstation to integrate robotic technology is far from being a linear and easy process. In this work, we explore this delicate balance between the ergonomic, production, and safety requirements in the design of a new collaborative cell. We explain the different steps of this digital transformation process and the thought process behind human-robot task allocation to maximize the collaborative robot efficiency while improving the work conditions. This work describes the development of a certified and production-ready collaborative workstation based on ergonomic criteria. Results show a significant reduction in the global ergonomic risk score associated with the workers' actions and postures and an increase in production quotas, compared to the previous manual process.This work was supported by NORTE-06-3559-FSE-000018, integrated into the invitation NORTE-59-2018-41, aiming to hire highly-qualified human resources, co-financed by the Regional Operational Programme of the North 2020, thematic area of Competitiveness and Employment, through the European Social Fund (ESF)

A framework for compliant physical interaction : the grasp meets the task

Although the grasp-task interplay in our daily life is unquestionable, very little research has addressed this problem in robotics. In order to fill the gap between the grasp and the task, we adopt the most successful approaches to grasp and task specification, and extend them with additional elements that allow to define a grasp-task link. We propose a global sensor-based framework for the specification and robust control of physical interaction tasks, where the grasp and the task are jointly considered on the basis of the task frame formalism and the knowledge-based approach to grasping. A physical interaction task planner is also presented, based on the new concept of task-oriented hand pre-shapes. The planner focuses on manipulation of articulated parts in home environments, and is able to specify automatically all the elements of a physical interaction task required by the proposed framework. Finally, several applications are described, showing the versatility of the proposed approach, and its suitability for the fast implementation of robust physical interaction tasks in very different robotic systems

Real-time failure-tolerant control of kinematically redundant manipulators

Includes bibliographical references.This work considers real-time fault-tolerant control of kinematically redundant manipulators to single locked-joint failures. The fault-tolerance measure used is a worst-case quantity, given by the minimum, over all single joint failures, of the minimum singular value of the post-failure Jacobians. Given any end-effector trajectory, the goal is to continuously follow this trajectory with the manipulator in configurations that maximize the fault-tolerance measure. The computation required to track these optimal configurations with brute-force methods is prohibitive for real-time implementation. We address this issue by presenting algorithms that quickly compute estimates of the worst-case fault-tolerance measure and its gradient. Real-time implementations are presented for all these techniques, and comparisons show that the performance of the best is indistinguishable from that of brute-force implementations.This work was supported by Sandia National Laboratories under contract number AL-3011

Real-time failure-tolerant control of kinematically redundant manipulators

Includes bibliographical references (pages 1115-1116).This work considers real-time fault-tolerant control of kinematically redundant manipulators to single locked-joint failures. The fault-tolerance measure used is a worst-case quantity, given by the minimum, over all single joint failures, of the minimum singular value of the post-failure Jacobians. Given any end-effector trajectory, the goal is to continuously follow this trajectory with the manipulator in configurations that maximize the fault-tolerance measure. The computation required to track these optimal configurations with brute-force methods is prohibitive for real-time implementation. We address this issue by presenting algorithms that quickly compute estimates of the worst-case fault-tolerance measure and its gradient. Comparisons show that the performance of the best method is indistinguishable from that of brute-force implementations. An example demonstrating the real-time performance of the algorithm on a commercially available seven degree-of-freedom manipulator is presented

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