Performance of modified jatropha oil in combination with hexagonal boron nitride particles as a bio-based lubricant for green machining

This study evaluates the machining performance of newly developed modified jatropha oils (MJO1, MJO3 and MJO5), both with and without hexagonal boron nitride (hBN) particles (ranging between 0.05 and 0.5 wt%) during turning of AISI 1045 using minimum quantity lubrication (MQL). The experimental results indicated that, viscosity improved with the increase in MJOs molar ratio and hBN concentration. Excellent tribological behaviours is found to correlated with a better machining performance were achieved by MJO5a with 0.05 wt%. The MJO5a sample showed the lowest values of cutting force, cutting temperature and surface roughness, with a prolonged tool life and less tool wear, qualifying itself to be a potential alternative to the synthetic ester, with regard to the environmental concern

Interactive Force Control Based on Multimodal Robot Skin for Physical Human-Robot Collaboration

This work proposes and realizes a control architecture that can support the deployment of a large-scale robot skin in a Human-Robot Collaboration scenario. It is shown, how whole-body tactile feedback can extend the capabilities of robots during dynamic interactions by providing information about multiple contacts across the robot\u27s surface. Specifically, an uncalibrated skin system is used to implement stable force control while simultaneously handling the multi-contact interactions of a user. The system formulates control tasks for force control, tactile guidance, collision avoidance, and compliance, and fuses them with a multi-priority redundancy resolution strategy. The approach is evaluated on an omnidirectional mobile-manipulator with dual arms covered with robot skin. Results are assessed under dynamic conditions, showing that multi-modal tactile information enables robust force control while at the same time remaining responsive to a user\u27s interactions

Development and Testing of a Software Framework for Controlling Humanoid Robots in Disaster-Response Scenarios

The aim of this thesis is to design and develop a modular software framework for controlling humanoid robots in teleoperation, in a context of disaster-response or civil defense. Over the years, natural (earthquakes, floods, etc.) or man-made disasters (nuclear reactor meltdowns, terrorist attacks, etc.) have caused several victims. The state of the art of disaster-robotics allows to deploy efficient and powerful robots in order to assist and support humans in the delicate phases of searching and rescuing survivors. In particular, with the use of teleoperation, the inclusion of a human operator (human-in-the-loop) can dramatically promote the application of humanoid robots, due to the human superior competence in critical thinking and context-awareness. This way, robots can be used as an interface between man and environment. Under these concepts, the thesis work focused on the design of a robust and efficient control architecture that brings whole-body locomotion and manipulation capabilities to the robot. Specifically, this thesis dealt with the development of a software module for teleoperating a robot while it is in a vehicle, making it able to drive. The module internal architecture is structured as a Finite State Machine, which allows to model a workflow of behaviors in an event-driven manner, providing safe and robust control in a teleoperation scenario. The effectiveness of the developed software has been validated during the DARPA Robotics Challenge Finals, occured in Pomona, CA (USA), on June 5-6 of 2015