scholarly journals 6D Virtual Sensor for Wrench Estimation in Robotized Interaction Tasks Exploiting Extended Kalman Filter

Machines ◽  
2020 ◽  
Vol 8 (4) ◽  
pp. 67
Author(s):  
Loris Roveda ◽  
Andrea Bussolan ◽  
Francesco Braghin ◽  
Dario Piga
Keyword(s):  
Kalman Filter ◽  
Extended Kalman Filter ◽  
Impedance Control ◽  
Human Robot Interaction ◽  
Industrial Robots ◽  
Virtual Sensor ◽  
Robot Controller ◽  
Interaction Control ◽  
Implementation Effort ◽  
High Bandwidth

Industrial robots are commonly used to perform interaction tasks (such as assemblies or polishing), requiring the robot to be in contact with the surrounding environment. Such environments are (partially) unknown to the robot controller. Therefore, there is the need to implement interaction controllers capable of suitably reacting to the established contacts. Although standard force controllers require force/torque measurements to close the loop, most of the industrial manipulators do not have installed force/torque sensor(s). In addition, the integration of external sensors results in additional costs and implementation effort, not affordable in many contexts/applications. To extend the use of compliant controllers to sensorless interaction control, a model-based methodology is presented in this paper for the online estimation of the interaction wrench, implementing a 6D virtual sensor. Relying on sensorless Cartesian impedance control, an Extended Kalman Filter (EKF) is proposed for the interaction wrench estimation. The described approach has been validated in simulations, taking into account four different scenarios. In addition, experimental validation has been performed employing a Franka EMIKA panda robot. A human–robot interaction scenario and an assembly task have been considered to show the capabilities of the developed EKF, which is able to perform the estimation with high bandwidth, achieving convergence with limited errors.

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

2021 ◽  
Author(s):  
Loris Roveda ◽  
Dario Piga
Keyword(s):  
Impedance Control ◽  
Interaction Force ◽  
Industrial Robots ◽  
Force Estimation ◽  
Interaction Control ◽  
Stiffness Properties ◽  
Implementation Effort ◽  
Coupling Dynamics ◽  
And Control ◽  
Assembly Tasks

AbstractIndustrial 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.

Smooth adaptive hybrid impedance control for robotic contact force tracking in dynamic environments

2020 ◽  
Vol 47 (2) ◽  
pp. 231-242
Author(s):  
Hongli Cao ◽  
Ye He ◽  
Xiaoan Chen ◽  
Xue Zhao
Keyword(s):  
Contact Force ◽  
High Speed ◽  
Impedance Control ◽  
Tracking Error ◽  
Industrial Robots ◽  
Force Response ◽  
Impedance Function ◽  
Content Type ◽  
Robot Controller ◽  
Force Tracking

Purpose The purpose of this paper is to take transient contact force response, overshoots and steady-state force tracking error problems into account to form an excellent force controller. Design/methodology/approach The basic impedance function with a pre-PID tuner is designed to improve the force response. A dynamic adaptive adjustment function that combines the advantages of hybrid impedance and adaptive hybrid impedance control is presented to achieve both force overshoots suppressing and tracking ability. Findings The introduced pre-PID tuner impedance function can achieve more than the pure impedance function in aspects of converging to the desired value and reducing the force overshoots. The performance of force overshoots suppression and force tracking error are maintained by introducing the dynamic adaptive sigma adjustment function. The simulation and experimental results both show the achieved control performance by comparing with the previous control methods. Practical implications The implementation of the controller is easy and convenient in practical manufacture scenes that require force control using industrial robots. Originality/value A superior robot controller adapting to a variety of complex tasks owing to the following characteristics: maintenance of high-accuracy position tracking capability in free-space (basic capabilities of modern industrial robots); maintenance of high speed, stability and smooth contact performance in collision stage; and presentation of high-precision force tracking capability in steady contact.

An Extended Kalman Filter for Collision Detection During Manipulator Contact Tasks

2014 ◽  
Author(s):  
Andy Zelenak ◽  
Mitch Pryor ◽  
Kyle Schroeder
Keyword(s):  
Kalman Filter ◽  
Dynamic Model ◽  
Extended Kalman Filter ◽  
Collision Detection ◽  
Force Feedback ◽  
Industrial Robot ◽  
Detection Algorithm ◽  
Industrial Robots ◽  
Joint Torque ◽  
Contact Tasks

The development of control strategies that allow stiff industrial robots to operate safely in unstructured environments is a significant challenge. This paper integrates two strategies that improve safety for industrial manipulators in uncertain conditions. First, software compliance in the task space is implemented using force feedback. End-effector compliance is vital for many tasks, such as interacting with humans or manipulating uncertain payloads. Beyond compliance, a collision detection algorithm detects collisions based on joint torque deviation from a dynamic model. Collisions can be detected at any point along the manipulator via loading or impulse anomalies. Joint torque data is typically noisy, and the accuracy of the robot dynamic model is limited, so an Extended Kalman Filter (EKF) was developed to improve the torque estimates. Experiments and demonstrations were performed using a commercially available 7DOF industrial robot. The EKF improved collision detection during unplanned contact tasks, and the method described here is hardware agnostic and extensible.

High-bandwidth force and impedance control for industrial robots

Robotica ◽  
1998 ◽  
Vol 16 (1) ◽  
pp. 75-87 ◽  
Author(s):  
Eckhard Freund ◽  
Jürgen Pesara
Keyword(s):  
Force Control ◽  
Hybrid Control ◽  
Impedance Control ◽  
Industrial Robots ◽  
New Method ◽  
Control Methods ◽  
Robotic Grinding ◽  
High Bandwidth ◽  
High Control

Common geared industrial robots call for force control methods with special properties such as good rejection of frictional disturbances, smoothness of corrective motions, and more. A new method is presented which meets these requirements and provides a high control bandwidth. In the manner of hybrid control, directions of a task frame can be selected to be force, impedance or position controlled. A joint-based inner position loop and a superimposed predictive force controller are used. Practical results include data from a robotic grinding facility. Here, the controller proved robustness and good performance under rough conditions.

Development of Impedance Control Based Strategies for Light-Weight Manipulator Applications Involving Compliant Interacting Environments and Compliant Bases

2014 ◽  
Author(s):  
Loris Roveda ◽  
Federico Vicentini ◽  
Nicola Pedrocchi ◽  
Lorenzo Molinari Tosatti ◽  
Francesco Braghin
Keyword(s):  
Kalman Filter ◽  
Extended Kalman Filter ◽  
Impedance Control ◽  
Interaction Force ◽  
Position Estimation ◽  
Control Laws ◽  
Constant Stiffness ◽  
Base Position ◽  
On Line ◽  
Tracking Strategy

The paper defines impedance control based control laws for interaction tasks with environments of unknown geometrical and mechanical properties, both considering manipulators mounted on A) rigid and B) compliant bases. In A) a deformation-tracking strategy allows the control of a desired deformation of the target environment. In B) a force-tracking strategy allows the control of a desired interaction force. In both A) and B) the on-line estimation of the environment stiffness is required. Therefore, an Extended Kalman Filter is defined. In B) the on-line estimation of the robot base position is used as a feedback in the control loop. The compliant base is modelled as a second-order physical system with known parameters (offline identification) and the base position is estimated from the measure of interaction forces. The Extended Kalman Filter, the grounding position estimation and the defined control laws are validated in simulation and with experiments, especially dedicated to an insertion-assembly task with A) time-varing stiffness environment and B) constant stiffness environment.

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