Analysis and Transfer of Human Movement Manipulability in Industry-like Activities

Humans exhibit outstanding learning, planning and adaptation capabilities while performing different types of industrial tasks. Given some knowledge about the task requirements, humans are able to plan their limbs motion in anticipation of the execution of specific skills. For example, when an operator needs to drill a hole on a surface, the posture of her limbs varies to guarantee a stable configuration that is compatible with the drilling task specifications, e.g. exerting a force orthogonal to the surface. Therefore, we are interested in analyzing the human arms motion patterns in industrial activities. To do so, we build our analysis on the so-called manipulability ellipsoid, which captures a posture-dependent ability to perform motion and exert forces along different task directions. Through thorough analysis of the human movement manipulability, we found that the ellipsoid shape is task dependent and often provides more information about the human motion than classical manipulability indices. Moreover, we show how manipulability patterns can be transferred to robots by learning a probabilistic model and employing a manipulability tracking controller that acts on the task planning and execution according to predefined control hierarchies.Comment: Accepted for publication in IROS'20. Website: https://sites.google.com/view/manipulability/home . Video: https://youtu.be/q0GZwvwW9A

Design, analysis and kinematic control of highly redundant serial robotic arms

The use of robotic manipulators in industry has grown in the last decades to improve and speed up industrial processes. Industrial manipulators started to be investigated for machining tasks since they can cover larger workspaces, increasing the range of achievable operations and improving flexibility. The company Nimbl’Bot developed a new mechanism, or module, to build stiffer flexible serial modular robots for machining applications. This manipulator is a kinematic redundant robot with 21 degrees of freedom. This thesis thoroughly analysis the Nimbl’Bot robot features and is divided into three main topics. The first topic regards using a task priority kinematic redundancy resolution algorithm for the Nimbl’Bot robot tracking trajectory while optimizing its kinetostatic performances. The second topic is the kinematic redundant robot design optimization with respect to a desired application and its kinetostatic performance. For the third topic, a new workspace determination algorithm is proposed for kinematic redundant manipulators. Several simulation tests are proposed and tested on some Nimbl’Bot robot designs for each subjects

Robotic Assistant Systems for Otolaryngology-Head and Neck Surgery

Recently, there has been a significant movement in otolaryngology-head and neck surgery (OHNS) toward minimally invasive techniques, particularly those utilizing natural orifices. However, while these techniques can reduce the risk of complications encountered with classic open approaches such as scarring, infection, and damage to healthy tissue in order to access the surgical site, there remain significant challenges in both visualization and manipulation, including poor sensory feedback, reduced visibility, limited working area, and decreased precision due to long instruments. This work presents two robotic assistance systems which help to overcome different aspects of these challenges. The first is the Robotic Endo-Laryngeal Flexible (Robo-ELF) Scope, which assists surgeons in manipulating flexible endoscopes. Flexible endoscopes can provide superior visualization compared to microscopes or rigid endoscopes by allowing views not constrained by line-of-sight. However, they are seldom used in the operating room due to the difficulty in precisely manually manipulating and stabilizing them for long periods of time. The Robo-ELF Scope enables stable, precise robotic manipulation for flexible scopes and frees the surgeon’s hands to operate bimanually. The Robo-ELF Scope has been demonstrated and evaluated in human cadavers and is moving toward a human subjects study. The second is the Robotic Ear Nose and Throat Microsurgery System (REMS), which assists surgeons in manipulating rigid instruments and endoscopes. There are two main types of challenges involved in manipulating rigid instruments: reduced precision from hand tremor amplified by long instruments, and difficulty navigating through complex anatomy surrounded by sensitive structures. The REMS enables precise manipulation by allowing the surgeon to hold the surgical instrument while filtering unwanted movement such as hand tremor. The REMS also enables augmented navigation by calculating the position of the instrument with high accuracy, and combining this information with registered preoperative imaging data to enforce virtual safety barriers around sensitive anatomy. The REMS has been demonstrated and evaluated in user studies with synthetic phantoms and human cadavers

A user study on personalized stiffness control and task specificity in physical Human-Robot Interaction

Gopinathan S, Ötting SK, Steil JJ. A user study on personalized stiffness control and task specificity in physical Human-Robot Interaction. Frontiers in Robotics and AI. 2017;4: 58.An ideal physical human–robot interaction (pHRI) should offer the users robotic systems that are easy to handle, intuitive to use, ergonomic and adaptive to human habits and preferences. But the variance in the user behavior is often high and rather unpredictable, which hinders the development of such systems. This article introduces a Personalized Adaptive Stiffness controller for pHRI that is calibrated for the user’s force profile and validates its performance in an extensive user study with 49 participants on two different tasks. The user study compares the new scheme to conventional fixed stiffness or gravitation compensation controllers on the 7-DOF KUKA LWR IVb by employing two typical joint-manipulation tasks. The results clearly point out the importance of considering task specific parameters and human specific parameters while designing control modes for pHRI. The analysis shows that for simpler tasks a standard fixed controller may perform sufficiently well and that respective task dependency strongly prevails over individual differences. In the more complex task, quantitative and qualitative results reveal differences between the respective control modes, where the Personalized Adaptive Stiffness controller excels in terms of both performance gain and user preference. Further analysis shows that human and task parameters can be combined and quantified by considering the manipulability of a simplified human arm model. The analysis of user’s interaction force profiles confirms this finding

Kinematics and Robot Design II (KaRD2019) and III (KaRD2020)

This volume collects papers published in two Special Issues “Kinematics and Robot Design II, KaRD2019” (https://www.mdpi.com/journal/robotics/special_issues/KRD2019) and “Kinematics and Robot Design III, KaRD2020” (https://www.mdpi.com/journal/robotics/special_issues/KaRD2020), which are the second and third issues of the KaRD Special Issue series hosted by the open access journal robotics.The KaRD series is an open environment where researchers present their works and discuss all topics focused on the many aspects that involve kinematics in the design of robotic/automatic systems. It aims at being an established reference for researchers in the field as other serial international conferences/publications are. Even though the KaRD series publishes one Special Issue per year, all the received papers are peer-reviewed as soon as they are submitted and, if accepted, they are immediately published in MDPI Robotics. Kinematics is so intimately related to the design of robotic/automatic systems that the admitted topics of the KaRD series practically cover all the subjects normally present in well-established international conferences on “mechanisms and robotics”.KaRD2019 together with KaRD2020 received 22 papers and, after the peer-review process, accepted only 17 papers. The accepted papers cover problems related to theoretical/computational kinematics, to biomedical engineering and to other design/applicative aspects

Contact aware robust semi-autonomous teleoperation of mobile manipulators

In the context of human-robot collaboration, cooperation and teaming, the use of mobile manipulators is widespread on applications involving unpredictable or hazardous environments for humans operators, like space operations, waste management and search and rescue on disaster scenarios. Applications where the manipulator's motion is controlled remotely by specialized operators. Teleoperation of manipulators is not a straightforward task, and in many practical cases represent a common source of failures. Common issues during the remote control of manipulators are: increasing control complexity with respect the mechanical degrees of freedom; inadequate or incomplete feedback to the user (i.e. limited visualization or knowledge of the environment); predefined motion directives may be incompatible with constraints or obstacles imposed by the environment. In the latter case, part of the manipulator may get trapped or blocked by some obstacle in the environment, failure that cannot be easily detected, isolated nor counteracted remotely. While control complexity can be reduced by the introduction of motion directives or by abstraction of the robot motion, the real-time constraint of the teleoperation task requires the transfer of the least possible amount of data over the system's network, thus limiting the number of physical sensors that can be used to model the environment. Therefore, it is of fundamental to define alternative perceptive strategies to accurately characterize different interaction with the environment without relying on specific sensory technologies. In this work, we present a novel approach for safe teleoperation, that takes advantage of model based proprioceptive measurement of the robot dynamics to robustly identify unexpected collisions or contact events with the environment. Each identified collision is translated on-the-fly into a set of local motion constraints, allowing the exploitation of the system redundancies for the computation of intelligent control laws for automatic reaction, without requiring human intervention and minimizing the disturbance of the task execution (or, equivalently, the operator efforts). More precisely, the described system consist in two different building blocks. The first, for detecting unexpected interactions with the environment (perceptive block). The second, for intelligent and autonomous reaction after the stimulus (control block). The perceptive block is responsible of the contact event identification. In short, the approach is based on the claim that a sensorless collision detection method for robot manipulators can be extended to the field of mobile manipulators, by embedding it within a statistical learning framework. The control deals with the intelligent and autonomous reaction after the contact or impact with the environment occurs, and consist on an motion abstraction controller with a prioritized set of constrains, where the highest priority correspond to the robot reconfiguration after a collision is detected; when all related dynamical effects have been compensated, the controller switch again to the basic control mode

Haptic Guidance for Extended Range Telepresence

A novel navigation assistance for extended range telepresence is presented. The haptic information from the target environment is augmented with guidance commands to assist the user in reaching desired goals in the arbitrarily large target environment from the spatially restricted user environment. Furthermore, a semi-mobile haptic interface was developed, one whose lightweight design and setup configuration atop the user provide for an absolutely safe operation and high force display quality

Shear-promoted drug encapsulation into red blood cells: a CFD model and μ-PIV analysis

The present work focuses on the main parameters that influence shear-promoted encapsulation of drugs into erythrocytes. A CFD model was built to investigate the fluid dynamics of a suspension of particles flowing in a commercial micro channel. Micro Particle Image Velocimetry (μ-PIV) allowed to take into account for the real properties of the red blood cell (RBC), thus having a deeper understanding of the process. Coupling these results with an analytical diffusion model, suitable working conditions were defined for different values of haematocrit

Robot Manipulators

Robot manipulators are developing more in the direction of industrial robots than of human workers. Recently, the applications of robot manipulators are spreading their focus, for example Da Vinci as a medical robot, ASIMO as a humanoid robot and so on. There are many research topics within the field of robot manipulators, e.g. motion planning, cooperation with a human, and fusion with external sensors like vision, haptic and force, etc. Moreover, these include both technical problems in the industry and theoretical problems in the academic fields. This book is a collection of papers presenting the latest research issues from around the world