Exploiting impedance shaping approaches to overcome force overshoots in delicate interaction tasks

Roveda, Loris; Pedrocchi, Nicola; Tosatti, Lorenzo Molinari

doi:10.1177/1729881416662771

Cited by 26 publications

(23 citation statements)

References 36 publications

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“…Considering interaction tasks (i.e., robot exchanging forces/torques with the environment), the capability to adapt to new scenarios becomes even more critical (Hogan 1984). To avoid any unwanted/unstable behavior, the interaction force has to be controlled (Vukobratovic 2010;Roveda et al 2016). Common interaction control strategies, however, make use of expensive sensors (Roveda et al 2018a;Roveda 2018;, increasing the hardware costs and the setup time.…”

Section: Contextmentioning

confidence: 99%

Sensorless environment stiffness and interaction force estimation for impedance control tuning in robotized interaction tasks

Roveda

Piga

2021

Auton Robot

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Industrial robots are increasingly used to perform tasks requiring an interaction with the surrounding environment (e.g., assembly tasks). Such environments are usually (partially) unknown to the robot, requiring the implemented controllers to suitably react to the established interaction. Standard controllers require force/torque measurements to close the loop. However, most of the industrial manipulators do not have embedded force/torque sensor(s) and such integration results in additional costs and implementation effort. To extend the use of compliant controllers to sensorless interaction control, a model-based methodology is presented in this paper. Relying on sensorless Cartesian impedance control, two Extended Kalman Filters (EKF) are proposed: an EKF for interaction force estimation and an EKF for environment stiffness estimation. Exploiting such estimations, a control architecture is proposed to implement a sensorless force loop (exploiting the provided estimated force) with adaptive Cartesian impedance control and coupling dynamics compensation (exploiting the provided estimated environment stiffness). The described approach has been validated in both simulations and experiments. A Franka EMIKA panda robot has been used. A probing task involving different materials (i.e., with different - unknown - stiffness properties) has been considered to show the capabilities of the developed EKFs (able to converge with limited errors) and control tuning (preserving stability). Additionally, a polishing-like task and an assembly task have been implemented to show the achieved performance of the proposed methodology.

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Section: Contextmentioning

confidence: 99%

Sensorless environment stiffness and interaction force estimation for impedance control tuning in robotized interaction tasks

Roveda

Piga

2021

Auton Robot

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“…To avoid any undesired or unstable behavior, the interaction has to be controlled Vukobratovic (2010). Common interaction control strategies make use of external sensors Roveda et al (2016), Roveda et al (2018), Roveda (2018), Polverini et al (2019). However, such a solution increases the hardware costs and the setup time of the robotic cell.…”

Section: Contextmentioning

confidence: 99%

Robust state dependent Riccati equation variable impedance control for robotic force-tracking tasks

Roveda

Piga

2020

Int J Intell Robot Appl

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Industrial robots are increasingly used in highly flexible interaction tasks, where the intrinsic variability makes difficult to pre-program the manipulator for all the different scenarios. In such applications, interaction environments are commonly (partially) unknown to the robot, requiring the implemented controllers to take in charge for the stability of the interaction. While standard controllers are sensor-based, there is a growing need to make sensorless robots (i.e., most of the commercial robots are not equipped with force/torque sensors) able to sense the environment, properly reacting to the established interaction. This paper proposes a new methodology to sensorless force control manipulators. On the basis of sensorless Cartesian impedance control, an Extended Kalman Filter (EKF) is designed to estimate the interaction exchanged between the robot and the environment. Such an estimation is then used in order to close a robust high-performance force loop, designed exploiting a variable impedance control and a State Dependent Riccati Equation (SDRE) force controller. The described approach has been validated in simulations. A Franka EMIKA panda robot has been considered as a test platform. A probing task involving different materials (i.e., with different stiffness properties) has been considered to show the capabilities of the developed EKF (able to converge with limited errors) and controller (preserving stability and avoiding overshoots). The proposed controller has been compared with an LQR controller to show its improved performance.

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“…A through-thearm system tracks the desired force by adjusting the whole robot's posture, but its high inertia inevitably leads to a slow response for force control [6]. To improve the force tracking accuracy of this method, Loris Roveda proposed an on-line estimation of the interactive environment stiffness between the robot and the workpiece [18] and a discrete-time formulation for impedance controlled tasks [19] to overcome the force overshoot issue. Whereas an around-the-arm system forms a macro-mini robotic system ( Fig.…”

Section: Introductionmentioning

confidence: 99%

A High-Bandwidth End-Effector With Active Force Control for Robotic Polishing

Guan

Chen

et al. 2020

IEEE Access

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To promote operational intelligence, improve surface quality, and reduce manpower dependence, a novel high-bandwidth end-effector with active force control for robotic polishing was proposed. Using this end-effector as a mini robot, a macro-mini robot for polishing processing was constructed, in which the macro robot provides posture control during polishing operations, whereas the mini-robot provides constant force control. By minimizing the inertia along the spindle in this configuration, the endeffector obtains a force control bandwidth of 200 Hz. Through a series of comparative experiments with different contact forces and feed rates, the proposed design was proven to have a smaller overshoot, a faster response, and a shorter settling time than the conventional method based on macro robot (KUKA iiwa) controlled force. The roughness of the workpiece reached 0.4 µm after polishing with the macro-mini robot, indicating the efficiency of this end-effector in high-precision material removal and surface polishing operations.

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Exploiting impedance shaping approaches to overcome force overshoots in delicate interaction tasks

Cited by 26 publications

References 36 publications

Sensorless environment stiffness and interaction force estimation for impedance control tuning in robotized interaction tasks

Sensorless environment stiffness and interaction force estimation for impedance control tuning in robotized interaction tasks

Robust state dependent Riccati equation variable impedance control for robotic force-tracking tasks

A High-Bandwidth End-Effector With Active Force Control for Robotic Polishing

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