Bilateral Teleoperation for Linear Force Sensorless 3D Robots

Abstract. It is well known that for bilateral teleoperation, force feedback information is needed. In this paper, we propose a control approach for bilateral teleoperation with uncertainties in the model of the slave robot and which does not use force sensors for haptic feedback. The controller design is based on a cyclic switching algorithm. In the first phase of the cyclic algorithm, we estimate the environmental force acting on the slave robot and in the second phase a tracking controller ensures that the position of the slave robot is tracking the position of the master robot. A stability analysis of the overall closed-loop system is presented and the approach is illustrated by means of an example

External force estimation for telerobotics without force sensor

This paper establishes an approach to external force estimation through the use of a mathematical model and current sensing, without employing a force/torque sensor. The advantages and need for force feedback have been well established in the field of telerobotics. This paper presents the requirement for sensorless force estimation and comparative results between a force sensor and the presented approach using an industrial robot. The approach presents not only a cost effective solution but also a solution for force sensing in hazardous environments, especially ionizing radiation prone environments where the dose rates limit the use of sensing equipment. The paper also discusses the applications and advantages presented by this work in various fields

Sensorless Haptic Force Feedback for Telemanipulation using two identical Delta Robots

Bilateral teleoperation allows users to interact with objects in remote environments by providing the operator with haptic feedback. In this thesis two control scheme have been implemented in order to guarantee stability and transparency to the system: a position-position control scheme with gravity and passivity compensation and a bilateral force sensorless acceleration control implemented with Kalman filters and disturbance observers. Both methods were tested using two identical Delta robot

Enabling Human-Robot Collaboration via Holistic Human Perception and Partner-Aware Control

As robotic technology advances, the barriers to the coexistence of humans and robots are slowly coming down. Application domains like elderly care, collaborative manufacturing, collaborative manipulation, etc., are considered the need of the hour, and progress in robotics holds the potential to address many societal challenges. The future socio-technical systems constitute of blended workforce with a symbiotic relationship between human and robot partners working collaboratively. This thesis attempts to address some of the research challenges in enabling human-robot collaboration. In particular, the challenge of a holistic perception of a human partner to continuously communicate his intentions and needs in real-time to a robot partner is crucial for the successful realization of a collaborative task. Towards that end, we present a holistic human perception framework for real-time monitoring of whole-body human motion and dynamics. On the other hand, the challenge of leveraging assistance from a human partner will lead to improved human-robot collaboration. In this direction, we attempt at methodically defining what constitutes assistance from a human partner and propose partner-aware robot control strategies to endow robots with the capacity to meaningfully engage in a collaborative task

Neural network enhanced robot tool identification and calibration for bilateral teleoperation

© 2013 IEEE. In teleoperated surgery, the transmission of force feedback from the remote environment to the surgeon at the local site requires the availability of reliable force information in the system. In general, a force sensor is mounted between the slave end-effector and the tool for measuring the interaction forces generated at the remote sites. Such as the acquired force value includes not only the interaction force but also the tool gravity. This paper presents a neural network (NN) enhanced robot tool identification and calibration for bilateral teleoperation. The goal of this experimental study is to implement and validate two different techniques for tool gravity identification using Curve Fitting (CF) and Artificial Neural Networks (ANNs), separately. After tool identification, calibration of multi-axis force sensor based on Singular Value Decomposition (SVD) approach is introduced for alignment of the forces acquired from the force sensor and acquired from the robot. Finally, a bilateral teleoperation experiment is demonstrated using a serial robot (LWR4+, KUKA, Germany) and a haptic manipulator (SIGMA 7, Force Dimension, Switzerland). Results demonstrated that the calibration of the force sensor after identifying tool gravity component by using ANN shows promising performance than using CF. Additionally, the transparency of the system was demonstrated using the force and position tracking between the master and slave manipulators

Hydraulisen puomin voimatakaisinkytketty etäohjaus

Teleoperation has been under study from the mid 1940s, when the first mechanical master-slave manipulators were built to allow safe handling of nuclear material within a hot cell. Since then, need to operate within dangerous, out of reach, uncomfortable, or hazardous environments has then motivated researchers to study teleoperation further. In this thesis, teleoperation of a hydraulic manipulator with electrically driven master manipulator was studied. The workspace of the hydraulic slave manipulator is 5 m in height and it can reach 3 m. The master manipulator has a workspace approximating full arm movement pivoting at the shoulder. Further, the slave manipulator is capable of lifting over 1000 kg, while the master manipulator can lift only 2 kg. Objective of this thesis is to implement virtual decomposition control (VDC) type controller to the master manipulator and create communication channel for the two manipulators. The VDC approach is a subsystem model based feedforward controller. Similar controller for the slave manipulator has been implemented previously. Performance of the developed teleoperation system will be evaluated with experimental implementation measuring the free space motion tracking in two degrees of freedom motion. Results from the experimental implementation indicate accurate motion tracking between the two manipulators. Experimental results indicate less than 15 mm position error between the two manipulators, which considering the size of the HIAB can be considered promising

Velocity control of mini-UAV using a helmet system

International audienceThe usage of a helmet to command a mini-unmanned aerial vehicle (mini-UAV), is a telepresence system that connects the operator to the vehicle. This paper proposes a system which remotely allows the connection of a pilot's head motion and the 3D movements of a mini-UAVs. Two velocity control algorithms have been tested in order to manipulate the system. Results demonstrate that these movements can be used as reference inputs of the controller of the mini-UAV