Paolo Tripicchio

Towards Smart Farming and Sustainable Agriculture with Drones

The use of drones in agriculture is becoming more and more popular. The paper presents a novel approach to distinguish between different fields plowing techniques by means of an RGB-D sensor. The presented system can be easily integrated in commercially available Unmanned Aerial Vehicles (UAVs). In order to successfully classify the plowing techniques, two different measurement algorithms have been developed. Experimental tests show that the proposed methodology is able to provide a good classification of the fields plowing depths.

Bilateral teleoperation under time-varying delay using wave variables

Any teleoperation system involving two distant devices is affected by communication delay due to the physical gap between the devices. Several approaches based on wave variables have already been proposed to deal with time-varying delay. However, these approaches are too conservative resulting in high degradation from the constant time delay case. In this paper, we propose a new control scheme for bilateral teleoperation under time-varying communication delay entirely developed in the wave variables domain. The proposed method minimizes the performance degradation from the constant time delay case. Experimental results show the validity of the proposed scheme.

Design and Development of a Hand Exoskeleton Robot for Active and Passive Rehabilitation

The present work, which describes the mechatronic design and development of a novel rehabilitation robotic exoskeleton hand, aims to present a solution for neuromusculoskeletal rehabilitation. It presents a full range of motion for all hand phalanges and was specifically designed to carry out position and force-position control for passive and active rehabilitation routines. System integration and preliminary clinical tests are also presented.

Integration of multimodal technologies for a rowing platform

This paper presents the integration of multimodal technologies to measure and transmit different variables and stimuli involved in the human motion analysis, both for the training and for the transfer of users skills achieved by means of a mechatronic rowing platform. Although the mechanical design is the core of this project, this paper describes the integration and interaction of two multimodal systems (the human being and the rowing platform). These systems works together using different sensors and methodologies directly integrated to the human body to obtain detailed information related to the synchronization and correlation among the trajectories, Proximal distance coupling, velocities, muscular activation and muscular force, transversal force in the oars and head position acquired through digital image processing and machine learning techniques. This information is evaluated and used in the rendering section through audio-tactile stimuli for the acceleration learning process

A novel human-machine interface for working machines operation

The future of working machines winks to semi autonomy and latest technological aids to improve the quality of operations as well as the easiness of specific tasks execution. This field can take great advantage of latest human-machine interface (HMI) technologies that has been applied in the last years in field like virtual environments and robotics. The present paper discusses a novel approach for interactive operation of working machines. The approach combines traditional controls with visual/vision and haptic interactions. A wearable projection system has been introduced with the purpose of describing a wide set of localized commands recognized by the systems vision module. A preliminary setup has been developed using a simplified demonstration platform. A test session applied to a manipulation robot is presented to evaluate the performance of the proposed solutions in terms of task effectiveness, neglect tolerance, interaction effort and usability of the human-machine interface.

A multimodal training platform for minimally invasive robotic surgery

This paper gives an overview of a multimodal training platform developed for minimally invasive robotic surgery, based on the DLR MiroSurge system. It describes the technological components and integration of the hardware and software platform and presents the first integrated training tasks that enable surgeons to get familiar with the robotic system. The training platform shares the same surgical operator workstation as MiroSurge and simulates the behaviour of the telemanipulator arms and the surgical instruments. Like the real system the training platform provides haptic feedback and 3D-vision. However instead of the real telemanipulator itself, a virtual environment with abstracted tasks is connected to the operator workstation. This allows reduction in costs, to provide various levels of difficulty, and to focus on the skills to be taught. Thus a training platform is presented that aims at training a surgeons skills in handling the robotic system MiroSurge rather than training surgery in general.

Virtual Laboratory: a virtual distributed platform to share and perform experiments

This paper presents a distributed platform that gives researchers a framework to develop and deploy multi modal enabled experiments (haptic, audio, 3d vision), share them on the network with other research institutes and cooperate or remotely teleoperate with partners during the experiments. It gives also the possibility to see and collect significant data to be analyzed so that its possible to achieve scientific results. All the experiments performed within the platform are real-time and fully interactive distinguishing the proposed Virtual Laboratory from other virtual laboratories that is possible to find in literature. The purpose of such platform is to enhance the speed of development of multi modal haptic enabled applications and improve the whole scientific experiment workflow. In particular the Virtual Laboratory platform is intended to supply a common shared place to perform inter-laboratories experiments and enhance the production of scientific results.

Towards an autonomous flying robot for inspections in open and constrained spaces

A Micro Aerial Vehicle (MAV) capable of navigating in outdoor environments by means of proprioceptive data fusion techniques as well as in indoor and particularly in constrained spaces is here presented. The aim of this system is to inspect failures or procedures correctness inside dangerous areas where human presence should be avoided for long or short time periods. This solution has been oriented toward the specific context of visual inspection of industrial area and it has been tested in a laboratory testbed. In this paper we present hardware and software development of a MAV that can reliably navigate both in outdoor and indoor scenarios making it possible to autonomously change the working location.

Stacked generalization for scene analysis and object recognition

The problem of object recognition and detection has been largely addressed by the robotics community, since its importance both in mapping and manipulation problems. One possible approach for the recognition task is to assume a specific a-priori knowledge of the objects possibly present in a scene. In this framework, this paper presents a novel technique for object detection and recognition based on Stacked Generalization (SG) method developed by Wolpert in 1992. The innovation of the proposed technique is the introduction of SG classification method to perform a multi-layer object recognition fusing heterogeneous spatial and color data acquired with an RGB-D camera. To improve the accuracy and the robustness of the system to environmental variability, we introduce a second layer classifier. Its goal is to evaluate and weights the results of the first layer classifiers, thus combining and improving the overall classification performance. This technique has a low computational cost and is suitable for on-line applications, such as robotic manipulation or automated logistic systems. To validate the presented approach experimental tests have been carried out and results are reported.

Energy recovery in time-varying delay teleoperated system using wave-variables

While control theory for bilateral teleoperation systems under constant time communication delay is well developed, the research on time-varying communication delay systems is still ongoing. Most wave-based approaches proposed in literature to deal with time-varying delay appear too conservative resulting in high degradation from the constant time delay case. We have already proposed a bilateral control scheme with energy balance monitoring over packet switched communication networks. In the previous work, we dealt with a simplify situation where the time-varying was in the communication channel from master to the slave. However, we did not implement and test the system with a more complex scenario in which the delay was in both communication paths. The paper presents a complete bilateral teleoperation control scheme to compensate nonlinearity introduced by an Internet like communication channel. The system implements intelligent strategies to maintain the system passivity while it deals with position drift compensation, packets loss and blackouts management. Experimental results using the proposed control scheme are shown.