Loris Roveda

Deformation-tracking impedance control in interaction with uncertain environments

A deformation-tracking impedance control strategy is discussed for applications where a manipulator interacts with environments of unknown geometrical and mechanical properties, especially with stiffness comparable to a controlled robot stiffness. Based on force-tracking impedance controls, the deformation-tracking strategy allows the control of a desired deformation of the target environment, requiring the on-line estimation of the environment stiffness. An Extended Kalman Filter is used for the estimation of the environment because of measurement uncertainties and errors in compound interaction model. The tasks presented involve full body spatial interactions with a time-varying environment stiffness. The Extended Kalman Filter and the deformation-tracking impedance control are validated in simulation and with experiments. In particular, a cooperative assembly task is also performed with a human operator acting as varying environment, i.e. unpredictably changing the handling arm stiffness.

Optimal Impedance Force-Tracking Control Design With Impact Formulation for Interaction Tasks

The letter presents a force-tracking impedance controller granting a free-overshoots contact force (mandatory performance for many critical interaction tasks such as polishing) for partially unknown interacting environments (such as leather or hard-fragile materials). As in many applications, the robot has to gently approach the target environment (whose position is usually not well-known), then execute the interaction task. Therefore, the algorithm has been designed to deal with both the free space approaching motion (phase a.) and the succeeding contact task (phase b.) without switching from different control logics. Control gains have to be properly calculated for each phase in order to achieve the target force tracking performance (i.e., free-overshoots contact force). In detail, phase a. control gains are optimized based on the impact collision model to minimize the force error during the following contact task, while phase b. control gains are analytically calculated based on the solution of the LQR optimal control problem. The analytical solution grants the continuous adaptation of the control gains during the contact phase on the estimated value of the environment stiffness (obtained through an on-line extended Kalman filter). A probing task has been carried out to validate the performance of the control with partially unknown contact environment properties. Results show the avoidance of force overshoots and instabilities.

Impedance shaping controller for robotic applications in interaction with compliant environments

The impedance shaping control is presented in this paper, providing an extension of standard impedance controller. The method has been conceived to avoid force overshoots in applications where there is the need to track a force reference. Force tracking performance are obtained tuning on-line both the position set-point and the stiffness and damping parameters, based on the force error and on the estimated stiffness of the interacting environment (an Extended Kalman Filter is used). The stability of the presented strategy has been studied through Lyapunov. To validate the performance of the control an assembly task is taken into account, considering the geometrical and mechanical properties of the environment (partially) unknown. Results are compared with constant stiffness and damping impedance controllers, which show force overshoots and instabilities.

Impedance Control based Force-tracking Algorithm for Interaction Robotics Tasks: An Analytically Force Overshoots-free Approach

In the presented paper an analytically force overshoots-free approach is described for the execution of robotics interaction tasks involving a compliant (of unknown geometrical and mechanical properties) environment. Based on the impedance control, the aim of the work is to perform force-tracking applications avoiding force overshoots that may result in task failures. The developed algorithm shapes the equivalent stiffness and damping of the closed-loop manipulator to regulate the interaction dynamics deforming the impedance control set-point. The force-tracking performance are obtained defining the control gains analytically based on the estimation of the interacting environment stiffness (performed using an Extended Kalman Filter). The method has been validated in a probing task, showing the avoidance of force overshoots and the achieved target dynamic performance.

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

The aim of the presented article is to overcome the force overshoot issue in impedance based force tracking applications. Nowadays, light-weight manipulators are involved in high-accurate force control applications (such as polishing tasks), where the force overshoot issue is critical (i.e. damaging the component causing a production waste), exploiting the impedance control. Two main force tracking impedance control approaches are described in literature: (a) set-point deformation and (b) variable stiffness approaches. However, no contributions are directly related to the force overshoot issue. The presented article extends both such methodologies to analytically achieve the force overshoots avoidance in interaction tasks based on the on-line estimation of the interacting environment stiffness (available through an EKF). Both the proposed control algorithms allow to achieve a linear closed-loop dynamics for the coupled robot-environment system. Therefore, control gains can be analytically on-line calculated to achieve an over-damped closed-loop dynamics of the controlled coupled system. Control strategies have been validated in experiments, involving a KUKA LWR 4+. A probing task has been performed, representative of many industrial tasks (e.g. assembly tasks), in which a main force task direction is defined.

Force-tracking impedance control for manipulators mounted on compliant bases

The paper presents a control law for interaction tasks with environments of unknown geometrical and mechanical properties by manipulators mounted on compliant bases. Based on force-tracking impedance controls, the control strategy allows the execution of such class of tasks using the estimation of base position as a feedback in the control loop, requiring at the same time the on-line estimation of the environment stiffness. The properties of the control using non co-located sensors and the dynamic configuration of the coupled baserobot-environment system are studied. An Extended Kalman Filter is used for the estimation of the environment because of measurement uncertainties and errors in compound interaction model. The base is modelled as a second-order physical system with known parameters (offline identification before the task execution) and the base position is estimated from the measure of interaction forces. The grounding position estimation and the defined control law are validated in simulation and with experiments, especially dedicated to an insertion-assembly task. Control laws with and without the base compensation in the feedback loop are compared, verifying the effectiveness of the developed control law.

Impedance shaping controller for robotic applications involving interacting compliant environments and compliant robot bases

The impedance shaping control with robot base dynamics compensation is presented in this paper. The method has been conceived to avoid force overshoots in applications where the coupled dynamics of the global system (compliant robot base - controlled robot - interacting compliant environment) affects the force tracking task. Force tracking performance are obtained tuning on-line both the position set-point and the stiffness and damping parameters, based on the force error, the estimated stiffness of the interacting environment (an Extended Kalman Filter is used) and the estimated robot base position (a Kalman Filter is used). The stability of the presented strategy has been studied through Lyapunov. To validate the performance of the control an assembly task is taken into account, considering the geometrical and mechanical properties of the (partially) unknown environment. Results are compared with constant stiffness and damping impedance controllers, which show force overshoots and instabilities.

DEVELOPMENT OF IMPEDANCE CONTROL BASED STRATEGIES FOR LIGHT-WEIGHT MANIPULATOR APPLICATIONS INVOLVING COMPLIANT INTERACTING ENVIRONMENTS AND COMPLIANT BASES

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.Copyright

Discrete-Time Formulation for Optimal Impact Control in Interaction Tasks

Lightweight manipulators are increasingly involved in industrial scenarios due to their intrinsic safety features allowing to share working space and to cooperate with humans/robots. In particular, interaction tasks are one of their main application. In fact, by imposing a compliant behavior (at software or hardware level) a target interaction can be tracked while ensuring safety during the whole task. Despite the wide range of control strategies developed to face the interaction control problem, the limited control frequency and the measurements noise (especially considering the estimation of end-effector wrenchs from joint side measurements/estimation) are the main limitation in order to achieve improved interaction tracking performance. This paper presents a discrete time formulation for impedance controlled tasks granting a free-overshoot contact force throughout the whole contact phase between the robot and a partially unknown environment, involving finite sampling and force measurements filtering. Moreover, since many applications require the manipulator to approach the not well-known positioned target environment, the proposed algorithm is capable to avoid any force overshoot during the initial contact phase, taking into account non-zero approaching velocities. The main control structure is used in both the free-motion and contact phases, without switching from different control laws, by properly optimizing the control gains solving the defined LQR optimal control problem. A probing task has been carried out in order to validate the control performance with particular attention to the smoothness of the response. Results show the avoidance of force overshoots and instabilities. Moreover, the method has been compared to a continuous time control algorithm, showing improved performance.

Iterative Learning Procedure With Reinforcement for High-Accuracy Force Tracking in Robotized Tasks

The paper focuses on industrial interaction robotics tasks, investigating a control approach involving multiples learning levels for training the manipulator to execute a repetitive (partially) changeable task, accurately controlling the interaction. Based on compliance control, the proposed approach consists of two main control levels: 1) iterative friction learning compensation controller with reinforcement and 2) iterative force-tracking learning controller with reinforcement. The learning algorithms rely on the iterative learning and reinforcement learning procedures to automatize the controllers parameters tuning. The proposed procedure has been applied to an automotive industrial assembly task. A standard industrial UR 10 Universal Robot has been used, equipped by a compliant pneumatic gripper and a force/torque sensor at the robot end-effector.