A cloud robotics architecture for an emergency management and monitoring service in a smart cityenvironment

Cloud robotics is revolutionizing not only the robotics industry but also the ICT world, giving robots more storage and computing capacity, opening new scenarios that blend the physical to the digital world. In this vision new IT architectures are required to manage robots, retrieve data from them and create services to interact with users. In this paper a possible implementation of a cloud robotics architecture for the interaction between users and UAVs is described. Using the latter as monitoring agents, a service for fighting crime in urban environment is proposed, making one step forward towards the idea of smart cit

Tracking a Subset of Skeleton Joints: An Effective Approach towards Complex Human Activity Recognition

We present a robust algorithm for complex human activity recognition for natural human-robot interaction. The algorithm is based on tracking the position of selected joints in human skeleton. For any given activity, only a few skeleton joints are involved in performing the activity, so a subset of joints contributing the most towards the activity is selected. Our approach of tracking a subset of skeleton joints (instead of tracking the whole skeleton) is computationally efficient and provides better recognition accuracy. We have developed both manual and automatic approaches for the selection of these joints. The position of the selected joints is tracked for the duration of the activity and is used to construct feature vectors for each activity. Once the feature vectors have been constructed, we use a Support Vector Machines (SVM) multiclass classifier for training and testing the algorithm. The algorithm has been tested on a purposely built dataset of depth videos recorded using Kinect camera. The dataset consists of 250 videos of 10 different activities being performed by different users. Experimental results show classification accuracy of 83% when tracking all skeleton joints, 95% when using manual selection of subset joints, and 89% when using automatic selection of subset joints

Sensor Data Fusion using Unscented Kalman Filter for VOR-based Vision Tracking System for Mobile Robots

This paper presents sensor data fusion using Unscented Kalman Filter (UKF) to implement high performance vestibulo-ocular reflex (VOR) based vision tracking system for mobile robots. Information from various sensors is required to be integrated using an efficient sensor fusion algorithm to achieve a continuous and robust vision tracking system. We use data from low cost accelerometer, gyroscope, and encoders to calculate robot motion information. The Unscented Kalman Filter is used as an efficient sensor fusion algorithm. The UKF is an advanced filtering technique which outperforms widely used Extended Kalman Filter (EKF) in many applications. The system is able to compensate for the slip errors by switching between two different UKF models built for slip and no-slip cases. Since the accelerometer error accumulates with time because of the double integration, the system uses accelerometer data only for the slip case UKF model. Using sensor fusion by UKF, the position and orientation of the robot is estimated and is used to rotate the camera mounted on top of the robot towards a fixed target. This concept is derived from the vestibule-ocular reflex (VOR) of the human eye. The experimental results show that the system is able to track the fixed target in various robot motion scenarios including the scenario when an intentional slip is generated during robot navigation

A cloud robotics architecture for an emergency management and monitoring service in a smart cityenvironment

Cloud robotics is revolutionizing not only the robotics industry but also the ICT world, giving robots more storage and computing capacity, opening new scenarios that blend the physical to the digital world. In this vision new IT architectures are required to manage robots, retrieve data from them and create services to interact with users. In this paper a possible implementation of a cloud robotics architecture for the interaction between users and UAVs is described. Using the latter as monitoring agents, a service for fighting crime in urban environment is proposed, making one step forward towards the idea of smart city

A Low-cost Open Source 3D-Printable Dexterous Anthropomorphic Robotic Hand with a Parallel Spherical Joint Wrist for Sign Languages Reproduction

We present a novel open-source 3D-printable dexterous anthropomorphic robotic hand specifically designed to reproduce Sign Languages' hand poses for deaf and deaf-blind users. We improved the InMoov hand, enhancing dexterity by adding abduction/adduction degrees of freedom of three fingers (thumb, index and middle fingers) and a three-degrees-of-freedom parallel spherical joint wrist. A systematic kinematic analysis is provided. The proposed robotic hand is validated in the framework of the PARLOMA project. PARLOMA aims at developing a telecommunication system for deaf-blind people, enabling remote transmission of signs from tactile Sign Languages. Both hardware and software are provided online to promote further improvements from the community

Validation and verification of modular GNC by means of TAS-I robot management framework in outdoor rovers exploration facility

The objective of STEPS2 “Rover Surface Navigation” work package was the design, development, validation and verification of innovative solutions suitable for the future (manned and unmanned) space robotics mission. A particular focus has been put in the autonomous capabilities to be implemented for the baseline mission scenario: sample canister acquisition and return, simulated in TAS-I ROvers eXploration facilitY.This paper gives an overview of the adopted System Development Life Cycle, that is based on V-model and agile methodologies. Then the infrastructure, including the ROXY facility and research robots are detailed. The paper focuses on the Test activities and relevant results for the Modular GNC developed on the TAS-I Robot Management Framework architecture. Finally, the future envisaged activities are presented, including upgrades to Methodology, ROXY facility and GNC modules and their usage in the frame of TAS-I research activities and ESA funded contracts

Book Review "Intelligent Seam Tracking for Robotic Welding", by N. Nayak, A. Ray

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