Human-activity-centered measurement system:challenges from laboratory to the real environment in assistive gait wearable robotics

Assistive gait wearable robots (AGWR) have shown a great advancement in developing intelligent devices to assist human in their activities of daily living (ADLs). The rapid technological advancement in sensory technology, actuators, materials and computational intelligence has sped up this development process towards more practical and smart AGWR. However, most assistive gait wearable robots are still confined to be controlled, assessed indoor and within laboratory environments, limiting any potential to provide a real assistance and rehabilitation required to humans in the real environments. The gait assessment parameters play an important role not only in evaluating the patient progress and assistive device performance but also in controlling smart self-adaptable AGWR in real-time. The self-adaptable wearable robots must interactively conform to the changing environments and between users to provide optimal functionality and comfort. This paper discusses the performance parameters, such as comfortability, safety, adaptability, and energy consumption, which are required for the development of an intelligent AGWR for outdoor environments. The challenges to measuring the parameters using current systems for data collection and analysis using vision capture and wearable sensors are presented and discussed

Probabilistic identification of sit-to-stand and stand-to-sit with a wearable sensor

Identification of human movements is crucial for the design of intelligent devices capable to provide assistance. In this work, a Bayesian formulation, together with a sequential analysis method, is presented for identification of sit-to-stand (SiSt) and stand-to-sit (StSi) activities. This method performs autonomous iterative accumulation of sensor measurements and decision-making processes, while dealing with noise and uncertainty present in sensors. First, the Bayesian formulation is able to identify sit, transition and stand activity states. Second, the transition state, divided into transition phases, is used to identify the state of the human body during SiSt and StSi. These processes employ acceleration signals from an inertial measurement unit attached to the thigh of participants. Validation of our method with experiments in offline, real-time and a simulated environment, shows its capability to identify the human body during SiSt and StSi with an accuracy of 100% and mean response time of 50 ms (5 sensor measurements). In the simulated environment, our approach shows its potential to interact with low-level methods required for robot control. Overall, this work offers a robust framework for intelligent and autonomous systems, capable to recognise the human intent to rise from and sit on a chair, which is essential to provide accurate and fast assistance

Optimization of the investment casting process

Rapid prototyping is an important technique for manufacturing. This work refers to the manufacture of hollow patterns made of polymeric materials by rapid prototyping technologies for its use in the preparation of ceramic molds in the investment casting process. This work is focused on the development of a process for manufacturing patterns different from those that currently exist due to its hollow interior design, allowing its direct use in the fabrication of ceramic molds; avoiding cracking and fracture during the investment casting process, which is an important process for the foundry industry

Bayesian perception of touch for control of robot emotion

In this paper, we present a Bayesian approach for perception of touch and control of robot emotion. Touch is an important sensing modality for the development of social robots, and it is used in this work as stimulus through a human-robot interaction. A Bayesian framework is proposed for perception of various types of touch. This method together with a sequential analysis approach allow the robot to accumulate evidence from the interaction with humans to achieve accurate touch perception for adaptable control of robot emotions. Facial expressions are used to represent the emotions of the iCub humanoid. Emotions in the robotic platform, based on facial expressions, are handled by a control architecture that works with the output from the touch perception process. We validate the accuracy of our system with simulated and real robot touch experiments. Results from this work show that our method is suitable and accurate for perception of touch to control robot emotions, which is essential for the development of sociable robots

Optimiranje postupka kalupljenja u ljevačkom procesu

Rapid prototyping is an important technique for manufacturing. This work refers to the manufacture of hollow patterns made of polymeric materials by rapid prototyping technologies for its use in the preparation of ceramic molds in the investment casting process. This work is focused on the development of a process for manufacturing patterns different from those that currently exist due to its hollow interior design, allowing its direct use in the fabrication of ceramic molds; avoiding cracking and fracture during the investment casting process, which is an important process for the foundry industry.Brzo razvijanje prototipa važna je proizvodna tehnika. Ovaj se rad odnosi na proizvodnju šupljih kalupa izrađenih od polimerskih materijala pomoću tehnologija brzog razvijanja prototipa za uporabu u izradi keramičkih modela u postupku kalupljenja ljevačkog procesa. Ovaj rad je usmjeren na razvijanje postupka za proizvodnju kalupa drukčijih od onih kakvi trenutno postoje i to zbog svoje šuplje unutarnje izvedbe čime se omogućava izravna uporaba u izradi keramičkih modela te se izbje gava pucanje i lom tijekom postupka kalupljenja ljevačkog procesa koji predstavlja važan postupak u ljevaoničkoj industriji

Development of a Smart Modular Heat Recovery Unit Adaptable into a Ventilated Façade

This paper presents the designing aspects and first experimental characterization of an adaptable Smart Modular Heat Recovery Unit (SMHRU) developed under the scope of the E2VENT Project. This SMHRU is being designed as a part of an adaptable renovation module for the retrofitting of multi-storey residential building from the 60's, 70's across Europe that embeds the SMHRU and an energy storage system based on a phase change material. This heat recovery unit will be adjustable to be integrated into the ventilated façade cavity, and able to recover heat from ventilation air, preheating the ventilation air in winter and precooling it in summer. This will allow an efficient combination of consumption reduction and acceptable air indoor quality. The first part of the paper presents designing considerations and thermal stationary analysis of the heat recovery unit, which is based on experimental correlations obtained for air-to-air compact offset-strip-fin plate heat exchangers. Secondly CFD analysis of the distributor of the SMHRU is presented. Finally prototype first performance estimation based on experimental results is presented.This work has been developed under the project “E2VENT: Energy Efficient Ventilated Façades” funded by the Horizon 2020 framework of the European Union, Project No. 637261