Showing papers by "Paolo Rocco published in 2016"

Safety in Human-Robot Collaborative Manufacturing Environments: Metrics and Control

Abstract: New paradigms in industrial robotics no longer require physical separation between robotic manipulators and humans. Moreover, in order to optimize production, humans and robots are expected to collaborate to some extent. In this scenario, involving a shared environment between humans and robots, common motion generation algorithms might turn out to be inadequate for this purpose.

Accurate sensorless lead-through programming for lightweight robots in structured environments

Abstract: Nowadays, programming an industrial manipulator is a complex and time-consuming activity, and this prevents industrial robots from being massively used in companies characterized by high production flexibility and rapidly changing products. The introduction of sensor-based lead-through programming approaches (where the operator manually guides the robot to teach new positions), instead, allows to increase the speed and reduce the complexity of the programming phase, yielding an effective solution to enhance flexibility. Nevertheless, some drawbacks arise, like for instance lack of accuracy, need to ensure the human operator safety, and need for force/torque sensors (the standard devices adopted for lead-through programming) that are expensive, fragile and difficult to integrate in the robot controller.This paper presents a novel approach to lead-through robot programming. The proposed strategy does not rely on dedicated hardware since torques due to operator's forces are estimated using a model-based observer fed with joint position, joint velocity and motor current measures. On the basis of this information, the external forces applied to the manipulator are reconstructed. A voting system identifies the largest Cartesian component of the force/torque applied to the manipulator in order to obtain accurate lead-through programming via admittance control. Finally an optimization stage is introduced in order to track the joint position displacements computed by the admittance filter as much as possible, while enforcing obstacle avoidance constraints, actuation bounds and Tool Centre Point (TCP) operational space velocity limits. The proposed approach has been implemented and experimentally tested on an ABB dual-arm concept robot FRIDA. HighlightsEstimation of the most likely direction of robot TCP positional/orientational displacement.Accurate tracking whilst maintaining safety with respect to workspace obstacles.

Sensorless and constraint based peg-in-hole task execution with a dual-arm robot

Abstract: Fast and sensorless peg-in-hole insertion is a challenging task for a robotic manipulator. In order to deal with the peg-in-hole insertion problem without any need of an external force/torque sensor, this paper proposes to actively accomplish compliance in the insertion task relying on an admittance based control. This is combined with a real-time trajectory generator, by means of constraint based optimization, where a model-based sensorless observer of interaction forces is exploited. Experiments have been performed on an ABB dual-arm 7-DOF lightweight prototype robot to validate the proposed approach, with an insertion speed comparable to human manual execution and in presence of geometric uncertainty.

Implicit force control for an industrial robot based on stiffness estimation and compensation during motion

Abstract: Although force control algorithms have been studied for three decades, this technology is not largely exploited in industry yet. The present paper proposes a position-based adaptive force control strategy, that relies on a novel method for the on line estimation of the environment stiffness. The control design is targeted to industrial controller structures and it is theoretically proven to be robust to time varying estimation errors of the environment stiffness and joint friction disturbances. The estimation algorithm succeeds in identifying the environment stiffness even in presence of geometrical irregularities of the contact surface during motion. The identification and control approaches are experimentally validated on an industrial robot equipped with a force sensor.

Constraint-Based and Sensorless Force Control With an Application to a Lightweight Dual-Arm Robot

Abstract: The increasing demand for flexible robotized solutions in SMEs motivates the research on innovative and general control algorithms suitable for a large variety of applications. Particularly suited for this are constraint-based trajectory generation and control methods, which have been deeply investigated in the last decade. In this letter, we present an application of such a control framework for sensorless execution of a force control task as applied to a dual-arm redundant manipulator. Experiments and simulations confirm the effectiveness of the approach, even in the case of parametric uncertainties.

Reactive Constrained Model Predictive Control for Redundant Mobile Manipulators

Abstract: Research interest in redundant mobile manipulators has been constantly increasing during the last decade. The opportunities offered by the redundant degrees of freedom, together with the exploitation of the mobile base, would allow such robots to complete their main task while complying with additional tasks or constraints. These features would make it easier for robots to work in a partly unstructured and dynamic environment, thus increasing production flexibility. In this work, a reactive constraint-based control strategy for mobile manipulators is proposed, which accomplishes a positioning task while simultaneously avoiding unknown and unpredictable obstacles. Differently from other approaches, the trajectory is computed exclusively online, by exploiting the MPC method, without the need of a pre-planned path. Experimental verification on a KUKA youBot shows the applicability of the approach.

Performance improvement of implicit integral robot force control through constraint-based optimization

Abstract: Classical control approaches to robot force control have been extensively addressed by research in the last decades and are now considered a paradigm when dealing with force control for industrial robots. With this respect, the present paper exploits the capability of state-of-the-art Quadratic Programming (QP) solvers to specify a simple and intuitive constraint-based optimization strategy aiming at improving closed-loop performance of a classical force controller, such as the implicit force control with pure integral action for a position-controlled manipulator in contact with a compliant environment. The effectiveness of the proposed control strategy is experimentally validated on an industrial robot equipped with a force sensor.

Robust constraint-based control of robot manipulators: An application to a visual aided grasping task

Abstract: Despite the availability in the literature of several constraint-based motion generation algorithms, modest attention has been paid to their robustness with respect to noise, and more in general, to unstructured uncertainties. Especially in the case of sensor-related constraints, the envisaged robustness properties are clearly crucial to enforce the correct and expected behaviour of these algorithms. This paper contributes with a method to explicitly account for different sources of uncertainty. We also suggest a computational efficient way to consistently modify the constraint specification in order to obtain such robustness. An experimental verification on a visual aided grasping task, where visibility of the object is to be maintained, enlightens the benefits of the proposed approach in terms of achieving the desired robustness.

Collision Avoidance with Task Constraints and Kinematic Limitations for Dual Arm Robots

Abstract: Human-robot interaction (HRI) is a key element for diffusion of robotised production. Clear advantages in flexibility and productivity are possible, when the two operators are free to interact, as they are endowed with complementary skills. To achieve such a goal, safety systems capable of coping with task and robot constraints have to be designed. In this paper, a collision avoidance strategy, tackling consistency with task constraints and robot kinematic limitations, is proposed. Robot joint velocities are selected with a QP optimisation problem, minimising the difference from evasive velocities, while respecting task constraints. Integration with an industrial controller is discussed as well, while the strategy is experimentally validated on a dual arm industrial robot prototype, working in close interaction with a human.

Online planning of optimal trajectories on assigned paths with dynamic constraints for robot manipulators

Abstract: This paper addresses time-optimal path-constrained trajectory planning. Given a geometric path for a manipulator, this paper focuses on the selection of the time law along the path. This law minimizes the time required to complete the path and at the same time is consistent with constraints, both at kinematic and dynamic levels. To obtain the optimal law a decision algorithm for the acceleration along the path has been developed. Remarkably, the algorithm is amenable to online implementation, thus allowing for path replanning. An experimental validation on an ABB IRB140 robot is shown.

Performance evaluation of visual odometry using an industrial robot as ground truth

Abstract: Computer vision algorithms for object localization and tracking are largely used in industry and academic research. Nonetheless, the performance evaluation of these algorithms is still an open problem, because the common systems used as ground truth are expensive and often not available in industry or research labs. In this paper we propose a method to evaluate the performance of a visual odometry algorithm using an industrial robot. The parameters required for the comparison are estimated by reducing the problem to a Quadratically Constrained Quadratic Program. The method is applied to an experimental set up composed of a six degrees of freedom industrial robot and a commercial monocular camera.