1,721,145 research outputs found
An Optimization Approach for a Robust and Flexible Control in Collaborative Applications
No full textIn Human-Robot Collaboration, the robot operates in a highly dynamic environment. Thus, it is pivotal to guarantee the robust stability of the system during the interaction but also a high flexibility of the robot behavior in order to ensure safety and reactivity to the variable conditions of the collaborative scenario. In this paper we propose a control architecture capable of maximizing the flexibility of the robot while guaranteeing a stable behavior when physically interacting with the environment. This is achieved by combining an energy tank based variable admittance architecture with control barrier functions. The proposed architecture is experimentally validated on a collaborative robot
Unified Power and Admittance Adaptation for Safe and Effective Physical Interaction With Unmodelled Dynamic Environments
No full textWhen interacting with unmodelled dynamic systems, a robot controller should be capable of adapting online its behavior, in order to be robust to the changing environmental conditions. In the paradigm of passivity-based control, virtual energy tanks allow to perform such adaptations in a robustly stable way, by bounding the amount of energy allocated to the controller. Nevertheless, when the workspace is shared with human collaborators, additional limits have to be imposed to the power the system can exert, in order to guarantee the overall safety. These bounds are difficult to estimate a priori, might vary over time and can significantly affect task execution. In this letter, we tackle this problem by simultaneously adapting online the admittance and the power limits in the controller, ensuring both safety and task performance. Experimental results with a collaborative manipulator validate the presented framework
An actor-critic strategy for a safe and efficient human robot collaboration
No full textFulfilling the ISO/TS 15066 regulation is crucial for implementing a certifiable human-robot collaborative application. If not properly embedded in the definition of the control action for the robot, the application of ISO/TS 15066 requirements can lead to a conservative and inefficient behavior of the robot. In order to maximize the performance, in this paper we propose an approach based on Deep Reinforcement Learning (DRL) for integrating the safety standards in a collaborative application. The proposed strategy is experimentally validated
A Torque Controlled Approach for Virtual Remote Centre of Motion Implementation
No full textIn this paper, we propose a novel torque controller for the implementation virtual remote center of motion. The controller allows the system to implement the required behavior and guarantees the satisfaction of the remote center of motion constraint. Exploiting the Udwadia-Kalaba equation for constrained dynamic systems, the controller is synthesized considering the dynamic effect the constraint produces on the manipulator, achieving more effective control with respect to kinematic strategies, and allowing the implementation of compliance behaviors. Simulations and experimental validation with a KUKA LWR 4+ with 7 degrees of freedom has been performed to check the performances of the proposed controller. Results show the effectiveness of the proposed controller with different control action, and the capability to interact with the environment by implementing compliant motion control
Dynamic-based RCM Torque Controller for Robotic-Assisted Minimally Invasive Surgery
No full textIn this paper we propose a novel flexible and optimization-free controller for standard torque-controlled manipulator for Robotic-Assisted Minimally Invasive Surgery. A novel method has been developed to model the constraint introduced by the laparoscopic tool, i.e. the remote center of motion, exploiting closed chain manipulators theory, and the final controller was synthesized considering the effects the constraint produces at a dynamic level. A set of simulations has been performed in a trajectory tracking task to validate the performances of the proposed controller. Performances have been also tested in a real experimental scenario with a KUKA LWR 4+ with 7 degrees of freedom endowed with a laparoscopic-like tool. Results show the effectiveness of the proposed controller and its capability of modifying the trajectory in order to preserve the RCM constraint
A Null-space based Approach for a Safe and Effective Human-Robot Collaboration
No full textDuring physical human robot collaboration, it is important to be able to implement a time-varying interactive behaviour while ensuring robust stability. Admittance control and passivity theory can be exploited for achieving these objectives. Nevertheless, when the admittance dynamics is time-varying, it can happen that, for ensuring a passive and stable behaviour, some spurious dissipative effects have to be introduced in the admittance dynamics. These effects are perceived by the user and degrade the collaborative performance. In this paper we exploit the task redundancy of the manipulator in order to harvest energy in the null space and to avoid spurious dynamics on the admittance. The proposed architecture is validated by simulations and by experiments onto a collaborative robot
Efficient ISO/TS 15066 Compliance through Model Predictive Control
No full textIn the actual industrial scenarios, human operators and robots work together sharing the workspace. Such proximity requires special attention in ensuring safety for the human operator, which is often translated in collision avoidance behaviour or high speed reduction. Adhering safety however is not the only aspect that must be taken into account. For many tasks, such as welding, it is crucial to ensure that the robot performs exactly the planned path. To optimize robot performance while complying with safety regulations, this work introduces a novel optimal nonlinear control problem. It prioritizes path preservation, exploiting redundancy to minimize task execution time, while explicitly adhering to the constraints imposed by ISO/TS 15066. To achieve high-performance outcomes, the control problem is addressed using the Model Predictive Control (MPC) approach. The proposed strategy has been experimentally validated in both simulations and a real-world industrial task involving a Kuka LWR4+ robot
Online Smooth Trajectory Planning for Mobile Robots by Means of Nonlinear Filters
No full textThe paper presents a nonlinear filtering technique that can be adopted to generate smooth trajectories for mobile robotic applications. The proposed trajectory planner can be fully executed online by the robot control system, thanks to its inherently discrete-time behavior and to its limited computational requirement. The outputs of the nonlinear filter used as a trajectory planner include the derivatives of the desired position in the cartesian plane up to the third order. This allows the implementation of feedback linearization control schemes that can transform the dynamics of a mobile robot in a double chain of three integrators, exploiting the highest derivative of the filter’s output as a feedforward action. Finally, the paper reports experimental results obtained by the full implementation of the proposed trajectory planning and control scheme on a real unicycle-like robot
The Fiscal Governance Disorder of the Eurozone: Curing the Symptoms or Curing the Causes?
No full textIn the book chapter we discuss the extent to which the proposed solutions of fiscal governance in the EU, including the EU2020 agenda, are able to cure both economic disorders (imbalances and growth) currently characterising the health of the Eurozone system. In particular we rely on a micro-founded decomposition of productivity dynamics across countries in the eurozone to derive our main results.[...
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