Vincenzo Lippiello

Position-Based Visual Servoing in Industrial Multirobot Cells Using a Hybrid Camera Configuration

This paper deals with the problem of position-based visual servoing in a multiarm robotic cell equipped with a hybrid eye-in-hand/eye-to-hand multicamera system. The proposed approach is based on the real-time estimation of the pose of a target object by using the extended Kalman filter. The data provided by all the cameras are selected by a suitable algorithm on the basis of the prediction of the object self-occlusions, as well as of the mutual occlusions caused by the robot links and tools. Only an optimal subset of image features is considered for feature extraction, thus ensuring high estimation accuracy with a computational cost independent of the number of cameras. A salient feature of the paper is the implementation of the proposed approach to the case of a robotic cell composed of two industrial robot manipulators. Two different case studies are presented to test the effectiveness of the hybrid camera configuration and the robustness of the visual servoing algorithm with respect to the occurrence of occlusions

Exploiting redundancy in Cartesian impedance control of UAVs equipped with a robotic arm

A Cartesian impedance control for UAVs equipped with a robotic arm is presented in this paper. A dynamic relationship between generalized external forces acting on the structure and the system motion, which is specified in terms of Cartesian space coordinates, is provided. Through a suitable choice of such variables and with respect to a given task, thanks to the added degrees of freedom given by the robot arm attached to the UAV, it is possible to exploit the redundancy of the system so as to perform some useful subtasks. The hovering control of a quadrotor, equipped with a 3-DOF robotic arm and subject to contact forces and external disturbances acting on some points of the whole structure, is tested in a simulated case study.

Visual Grasp Planning for Unknown Objects Using a Multifingered Robotic Hand

A method for fast visual grasping of unknown objects with a multifingered robotic hand is presented in this paper. The algorithm is composed of an object surface reconstruction algorithm and a local grasp planner, evolving in parallel. The reconstruction algorithm makes use of images taken by a camera carried by the robot arm. A virtual elastic reconstruction surface is placed around the object. The surface shrinks toward the object until some points intercept the object visual hull. Then, attractive forces with respect to the border of the visual hull are generated so as to compensate for the elastic forces: when an equilibrium between those forces is reached, the surface takes the form of the object shape. Running in parallel to the reconstruction algorithm, the grasp planner moves the fingertips on the current available reconstruction surface, toward points which are optimal (in a local sense) with respect to a number of indices weighting both the grasp quality and the kinematics configuration of the hand. This method, referred to as parallel visual grasp, may represent a valid candidate for applications where online grasp planning is required. A number of experiments are presented, showing the effectiveness of the proposed approach.

Cartesian Impedance Control of a UAV with a Robotic Arm

Abstract The dynamic model of a UAV with an attached robotic arm is derived in a symbolic matrix form through the Euler-Lagrangian formalism. A Cartesian impedance control, which provides a dynamic relationship between external generalized forces acting on the structure and the system motion, is then designed. The hovering control of a quadrotor, equipped with a 3-DOF robotic arm and subject to contact forces and external disturbances, is tested in a simulated case study.

The SHERPA project: Smart collaboration between humans and ground-aerial robots for improving rescuing activities in alpine environments

The goal of the paper is to present the foreseen research activity of the European project “SHERPA” whose activities will start officially on February 1th 2013. The goal of SHERPA is to develop a mixed ground and aerial robotic platform to support search and rescue activities in a real-world hostile environment, like the alpine scenario that is specifically targeted in the project. Looking into the technological platform and the alpine rescuing scenario, we plan to address a number of research topics about cognition and control. What makes the project potentially very rich from a scientific viewpoint is the heterogeneity and the capabilities to be owned by the different actors of the SHERPA system: the human rescuer is the “busy genius”, working in team with the ground vehicle, as the “intelligent donkey”, and with the aerial platforms, i.e. the “trained wasps” and “patrolling hawks”. Indeed, the research activity focuses on how the “busy genius” and the “SHERPA animals” interact and collaborate with each other, with their own features and capabilities, toward the achievement of a common goal.

MAV indoor navigation based on a closed-form solution for absolute scale velocity estimation using Optical Flow and inertial data

A new vision-based obstacle avoidance technique for indoor navigation of Micro Aerial Vehicles (MAVs) is presented in this paper. The vehicle trajectory is modified according to the obstacles detected through the Depth Map of the surrounding environment, which is computed online using the Optical Flow provided by a single onboard omnidirectional camera. An existing closed-form solution for the absolute-scale velocity estimation based on visual correspondences and inertial measurements is generalized and here employed for the Depth Map estimation. Moreover, a dynamic region-of-interest for image features extraction and a self-limitation control for the navigation velocity are proposed to improve safety in view of the estimated vehicle velocity. The proposed solutions are validated by means of simulations.

Aerial service robotics: The AIRobots perspective

This paper presents the main vision and research activities of the ongoing European project AIRobots (Innovative Aerial Service Robot for Remote Inspection by Contact, www.airobots.eu). The goal of AIRobots is to develop a new generation of aerial service robots capable of supporting human beings in all those activities that require the ability to interact actively and safely with environments not constrained on ground but, indeed, airborne. Besides presenting the main ideas and the research activities within the three-year project, the paper shows the first technological outcomes obtained during the first year and a half of activity.

Position and orientation estimation based on Kalman filtering of stereo images

The estimation problem of the position and orientation of a moving object from visual measurements is considered. Extended Kalman filtering of a sequence of stereo images is used to recursively compute an implicit solution to the projection equations. The proposed approach is general and can be applied to whatever number of cameras are fixed in the workspace. Computer simulations are presented to demonstrate the effectiveness of the algorithm in the presence of noise and to test the robustness of the estimate when some feature points are dynamically lost. Different types of geometric distortion as well as quantization and calibration errors are considered.

A multilayer control for multirotor UAVs equipped with a servo robot arm

A multilayer architecture to control multirotor UAVs equipped with a servo robot arm is proposed in this paper. The main purpose is to control the aerial platform taking into account the presence of the moving manipulator. Three layers are considered in this work. First, a novel mechanism is proposed considering a moving battery to counterweight the statics of the robotic arm. Then, in order to overcome the mechanical limitations of the previous layer, the residual of the arm static effects on the UAV is computed and compensated through the given control thrust and torques. Finally, an estimator of external forces and moments acting on the aerial vehicle is considered and the estimations are fed back to the controller to compensate neglected aerodynamic effects and the arm dynamics. The performance of the proposed architecture has been experimentally evaluated.

An open architecture for sensory feedback control of a dual‐arm industrial robotic cell

Purpose – To present an open architecture for real‐time sensory feedback control of a dual‐arm industrial robotic cell. The setup is composed of two industrial robot manipulators equipped with force/torque sensors and pneumatic grippers, a vision system and a belt conveyor.Design/methodology/approach – The original industrial robot controllers have been replaced by a single PC with software running under a real‐time variant of the Linux operative system.Findings – The new control architecture allows advanced control schemes to be developed and tested for the single robots and for the dual‐arm robotic cell, including force control and visual servoing tasks.Originality/value – An advanced user interface and a simulation environment have been developed, which permit fast, safe and reliable prototyping of planning and control algorithms.