A Variable-Fractional Order Admittance Controller for pHRI

Applied Sciences

Intuitive and comfortable physical human–robot interaction (pHRI) can be realized by changing impedance/admittance parameters corresponding to human interaction. However, this dynamic adjustment may result in drastically changed system dynamics, which usually give rise to system instability. We introduce a power envelope regulation strategy designed to constrain the variability of admittance parameters, thereby ensuring system passivity and mitigating the risk of instability. Then, sliding mode control (SMC) is employed to yield stable and robust performance. A new sliding surface is proposed based on feedback linearization, which shows improved tracking performance and stability compared to a conventional sliding surface. The effectiveness of the proposed sliding surface and associated control is theoretically validated. Notably, our modified sliding surface works universally, regardless of the order of the desired admittance equation. The trade-off between system chattering and ro...

This paper presents the implementation of fractionalorder algorithms both for hybrid and cascade position/force control of robotic manipulators. The system performance and robustness is analyzed in the time and frequency domains. The effects joint backlash and flexibility are also investigated.

International Journal of Mechatronics and Automation, 2014

Over the past years, eRobotics has been proving itself to be a flexible and efficient approach to tackle highly complex issues in research and application areas of robotics and automation, including planetary exploration, orbital servicing, sustainable forest management and industrial manufacturing. One of the main objectives of eRobotics is to bring robotics know-how into the fields of virtual reality and simulation on the basis of a holistic simulation approach that swiftly adapts to new demands and lays the foundation for the development of new technologies. Following this line of ideas, we introduce in this paper a novel systematical and highly modular approach to endow an open-chain robot manipulator with adaptable joint admittance control on a robot simulator. A three-stage admittance, position and torque control is developed to provide a desired joint admittance when external torques are sensed. The joint admittance is adapted by inferring the human intension to accelerate and decelerate during interaction in an intuitive and simple fashion. Experiments carried out on a physical 7 DoF KUKA LWR 4+ reveal that the proposed approach substantially reduces the robot resistance felt by the operator, therefore enhancing considerably the ease of manipulation.

IEEE Transactions on Haptics, 2021

The goal of this article is to design an admittance controller for a robot to adaptively change its contribution to a collaborative manipulation task executed with a human partner to improve the task performance. This has been achieved by adaptive scaling of human force based on her/his movement intention while paying attention to the requirements of different task phases. In our approach, movement intentions of human are estimated from measured human force and velocity of manipulated object, and converted to a quantitative value using a fuzzy logic scheme. This value is then utilized as a variable gain in an admittance controller to adaptively adjust the contribution of robot to the task without changing the admittance time constant. We demonstrate the benefits of the proposed approach by a pHRI experiment utilizing Fitts' reaching movement task. The results of the experiment show that there is a) an optimum admittance time constant maximizing the human force amplification and b) a desirable admittance gain profile which leads to a more effective co-manipulation in terms of overall task performance.

Applied sciences, 2021

Featured Application: Potential applications of this research include: (a) the operator teaches the manipulator to implement complicated tasks, such as welding, whose purpose is to eliminate the path planning, or (b) the manipulator supports the operator to lift heavy objects up and down.

2019

Human-robot collaboration is an appealing solution to increase the flexibility of production lines. In this context, we propose a kinematic control strategy for dual-arm robotic platforms physically collaborating with human operators. Based on admittance control, our approach aims at improving the performance of object transportation tasks by acting on two levels: estimating and compensating gravity effects on one side, and considering human intention in the cooperative task space on the other. An experimental study using virtual reality reveals the effectiveness of our method in terms of reduced human energy expenditure.

A computational approach to the study of robotic manipulators can provide answers to some problems presenting the simulation as a powerful tool for the design and optimization, which can be used for modelling and control of nonlinear dynamic systems. This paper presents a simulator that allows the integer and fractional-order (FO) control of a dual-arm robotic system for cooperative manipulation of objects considering the existence of nonlinearity (i.e., dynamic phenomena) in the joints inherent to real manipulators such as backlash, friction, saturation and flexibility.

IEEE Transactions on Control Systems Technology, 2017

Co-robotics involves humans and robots working collaboratively, as a team. This requires Physical Human-Robot Interaction (pHRI) systems that can adapt to the preferences of different humans and have good robustness and stability properties. In this paper a new inner-loop/outer-loop robot controller formulation is developed that makes pHRI robust to changes in both co-robot and human user. First, an inner-loop controller with guaranteed robustness and stability causes a robot to behave like a prescribed admittance model. Second, an outerloop controller tunes the admittance model so that the robot system assists humans with varying levels of skill to achieve taskspecific objectives. This design technique cleanly separates robotspecific control from task performance objectives, and allows formal inclusion in an outer design of both an ideal task model and unknown human operator dynamics. Experimental results with the controllers running on a PR2 robot demonstrate the effectiveness of this approach. Index Terms-Admittance control, adaptive inverse filtering, physical human-robot interaction, pHRI, robot control.

2013 Fourth International Conference on Computing, Communications and Networking Technologies (ICCCNT), 2013

Achieving effective control over robot manipulator is practically very difficult, due to various structured and unstructured uncertainties. But proper control of the manipulators is useful for different applications such as assembly operations, handling machine tools, pick and place work, welding, spray painting etc. In this paper, a fractional order controller is proposed to obtain enhanced smooth control, in terms of error reduction and minimum settling time. To implement fractional order controller ninteger toolbox is used. Comparative analysis of simulated performance with conventional PID controller is presented, which emphasize that fractional order controller provides a better control for tracking of a two DOF robot manipulator.