Human-robot collaboration for safe object transportation using force feedback

[EN] This work presents an approach based on multi-task, non-conventional sliding mode control and admittance control for human-robot collaboration aimed at handling applications using force feedback. The proposed robot controller is based on three tasks with different priority levels in order to cooperatively perform the safe transportation of an object with a human operator. In particular, a high-priority task is developed using non-conventional sliding mode control to guarantee safe reference parameters imposed by the task, e.g., keeping a load at a desired orientation (to prevent spill out in the case of liquids, or to reduce undue stresses that may compromise fragile items). Moreover, a second task based on a hybrid admittance control algorithm is used for the human operator to guide the robot by means of a force sensor located at the robot tool. Finally, a third low-priority task is considered for redundant robots in order to use the remaining degrees of freedom of the robot to achieve a pre-set secondary goal (e.g., singularity avoidance, remaining close to a homing configuration for increased safety, etc.) by means of the gradient projection method. The main advantages of the proposed method are robustness and low computational cost. The applicability and effectiveness of the proposed approach are substantiated by experimental results using a redundant 7R manipulator: the Sawyer collaborative robot. (C) 2018 Elsevier B.V. All rights reserved.This work was supported in part by the Spanish Government under Project DPI2017-87656-C2-1-R, and the Generalitat Valenciana under Grants VALi+d APOSTD/2016/044 and BEST/2017/029.Solanes Galbis, JE.; Gracia Calandin, LI.; Muñoz-Benavent, P.; Valls Miro, J.; Carmichael, MG.; Tornero Montserrat, J. (2018). Human-robot collaboration for safe object transportation using force feedback. Robotics and Autonomous Systems. 107:196-208. https://doi.org/10.1016/j.robot.2018.06.003S19620810

A Haptic Surface Robot Interface for Large-Format Touchscreen Displays

This thesis presents the design for a novel haptic interface for large-format touchscreens. Techniques such as electrovibration, ultrasonic vibration, and external braked devices have been developed by other researchers to deliver haptic feedback to touchscreen users. However, these methods do not address the need for spatial constraints that only restrict user motion in the direction of the constraint. This technology gap contributes to the lack of haptic technology available for touchscreen-based upper-limb rehabilitation, despite the prevalent use of haptics in other forms of robotic rehabilitation. The goal of this thesis is to display kinesthetic haptic constraints to the touchscreen user in the form of boundaries and paths, which assist or challenge the user in interacting with the touchscreen. The presented prototype accomplishes this by steering a single wheel in contact with the display while remaining driven by the user. It employs a novel embedded force sensor, which it uses to measure the interaction force between the user and the touchscreen. The haptic response of the device is controlled using this force data to characterize user intent. The prototype can operate in a simulated free mode as well as simulate rigid and compliant obstacles and path constraints. A data architecture has been created to allow the prototype to be used as a peripheral add-on device which reacts to haptic environments created and modified on the touchscreen. The long-term goal of this work is to create a haptic system that enables a touchscreen-based rehabilitation platform for people with upper limb impairments

Learning and Reacting with Inaccurate Prediction: Applications to Autonomous Excavation

Motivated by autonomous excavation, this work investigates solutions to a class of problem where disturbance prediction is critical to overcoming poor performance of a feedback controller, but where the disturbance prediction is intrinsically inaccurate. Poor feedback controller performance is related to a fundamental control problem: there is only a limited amount of disturbance rejection that feedback compensation can provide. It is known, however, that predictive action can improve the disturbance rejection of a control system beyond the limitations of feedback. While prediction is desirable, the problem in excavation is that disturbance predictions are prone to error due to the variability and complexity of soil-tool interaction forces. This work proposes the use of iterative learning control to map the repetitive components of excavation forces into feedforward commands. Although feedforward action shows useful to improve excavation performance, the non-repetitive nature of soil-tool interaction forces is a source of inaccurate predictions. To explicitly address the use of imperfect predictive compensation, a disturbance observer is used to estimate the prediction error. To quantify inaccuracy in prediction, a feedforward model of excavation disturbances is interpreted as a communication channel that transmits corrupted disturbance previews, for which metrics based on the sensitivity function exist. During field trials the proposed method demonstrated the ability to iteratively achieve a desired dig geometry, independent of the initial feasibility of the excavation passes in relation to actuator saturation. Predictive commands adapted to different soil conditions and passes were repeated autonomously until a pre-specified finish quality of the trench was achieved. Evidence of improvement in disturbance rejection is presented as a comparison of sensitivity functions of systems with and without the use of predictive disturbance compensation

The Fifth NASA/DOD Controls-Structures Interaction Technology Conference, part 2

This publication is a compilation of the papers presented at the Fifth NASA/DoD Controls-Structures Interaction (CSI) Technology Conference held in Lake Tahoe, Nevada, March 3-5, 1992. The conference, which was jointly sponsored by the NASA Office of Aeronautics and Space Technology and the Department of Defense, was organized by the NASA Langley Research Center. The purpose of this conference was to report to industry, academia, and government agencies on the current status of controls-structures interaction technology. The agenda covered ground testing, integrated design, analysis, flight experiments and concepts