Learning Human-Robot Collaboration Insights through the Integration of Muscle Activity in Interaction Motion Models

Recent progress in human-robot collaboration makes fast and fluid interactions possible, even when human observations are partial and occluded. Methods like Interaction Probabilistic Movement Primitives (ProMP) model human trajectories through motion capture systems. However, such representation does not properly model tasks where similar motions handle different objects. Under current approaches, a robot would not adapt its pose and dynamics for proper handling. We integrate the use of Electromyography (EMG) into the Interaction ProMP framework and utilize muscular signals to augment the human observation representation. The contribution of our paper is increased task discernment when trajectories are similar but tools are different and require the robot to adjust its pose for proper handling. Interaction ProMPs are used with an augmented vector that integrates muscle activity. Augmented time-normalized trajectories are used in training to learn correlation parameters and robot motions are predicted by finding the best weight combination and temporal scaling for a task. Collaborative single task scenarios with similar motions but different objects were used and compared. For one experiment only joint angles were recorded, for the other EMG signals were additionally integrated. Task recognition was computed for both tasks. Observation state vectors with augmented EMG signals were able to completely identify differences across tasks, while the baseline method failed every time. Integrating EMG signals into collaborative tasks significantly increases the ability of the system to recognize nuances in the tasks that are otherwise imperceptible, up to 74.6% in our studies. Furthermore, the integration of EMG signals for collaboration also opens the door to a wide class of human-robot physical interactions based on haptic communication that has been largely unexploited in the field.Comment: 7 pages, 2 figures, 2 tables. As submitted to Humanoids 201

Creating Gender in Disney/Pixar\u27s WALL-E.

In this thesis I will look at Disney/Pixar’s creation and portrayal of gender in the film WALL-E. In particular I will be looking at two areas of interest: (1) The ways in which Disney/ Pixar anthropomorphizes and creates gender for WALL-E and EVE, the two main robots featured in the movie, and (2) whether or not Disney/Pixar’s representations of masculinity and femininity follow the stereotypical representations of male dominance or if this representations challenge this stereotype. In this chapter, I will begin with a brief overview of previous studies in the areas of anthropomorphism, gender representation in children’s media, and the effects of gender portrayal in children’s media. In Chapter 2 I will then move into a description of feminist criticism, the method by which I plan to analyze WALL-E. In Chapter 3, my analysis will be looking at Disney/Pixar’s creation of gender for WALL-E and EVE, the degree of male centeredness and male dominance present in WALL-E, and the ways in which females are marginalized and femininity is portrayed as non-normative

Context and intention for 3D human motion prediction: experimentation and user study in handover tasks

© 2022 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes,creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.In this work we present a novel attention deep learning model that uses context and human intention for 3D human body motion prediction in handover human-robot tasks. This model uses a multi-head attention architecture which incorporates as inputs the human motion, the robot end effector and the position of the obstacles. The outputs of the model are the predicted motion of the human body and the predicted human intention. We use this model to analyze a handover collaborative task with a robot where the robot is able to predict the future motion of the human and use this information in it’s planner. Several experiments are performed where human volunteers fill a standard poll to rate different features, taking into account when the robot uses the prediction versus when the robot doesn’t use the prediction.Work supported under the Spanish State Research Agency through the Maria de Maeztu Seal of Excellence to IRI (MDM-2016- 0656), the ROCOTRANSP project (PID2019-106702RB-C21 / AEI / 10.13039/501100011033)) and the EU project CANOPIES (H2020- ICT2020-2-101016906).Peer ReviewedPostprint (author's final draft

Interação humano-robô para a transferência de objetos

Mestrado em Engenharia MecânicaRobots come into physical contact with humans under a variety of circumstances to perform useful work. This thesis has the ambitious aim of contriving a solution that leads to a simple case of physical human-robot interaction, an object transfer task. Firstly, this work presents a review of the current research within the field of Human-Robot Interaction, where two approaches are distinguished, but simultaneously required: a pre-contact approximation and an interaction by contact. Further, to achieve the proposed objectives, this dissertation addresses a possible answer to three major problems: (1) The robot control to perform the inherent movements of the transfer assignment, (2) the human-robot pre interaction and (3) the interaction by contact. The capabilities of a 3D sensor and force/tactile sensors are explored in order to prepare the robot to handover an object and to control the robot gripper actions, correspondingly. The complete software development is supported by the Robot Operating System (ROS) framework. Finally, some experimental tests are conducted to validate the proposed solutions and to evaluate the system's performance. A possible transfer task is achieved, even if some refinements, improvements and extensions are required to improve the solution performance and range.Os robôs entram em contacto físico com os humanos sob uma variedade de circunstâncias para realizar trabalho útil. Esta dissertação tem como objetivo o desenvolvimento de uma solução que permita um caso simples de interação física humano-robô, uma tarefa de transferência de objetos. Inicialmente, este trabalho apresenta uma revisão da pesquisa corrente na área da interação humano-robô, onde duas abordagens são distinguíveis, mas simultaneamente necessárias: uma aproximação pré-contacto e uma interação pós-contacto. Seguindo esta linha de pensamento, para atingir os objetivos propostos, esta dissertação procura dar resposta a três grandes problemas: (1) O controlo do robô para que este desempenhe os movimentos inerentes á tarefa de transferência, (2) a pré-interação humano-robô e (3) a interação por contacto. As capacidades de um sensor 3D e de sensores de força são exploradas com o objetivo de preparar o robô para a transferência e de controlar as ações da garra robótica, correspondentemente. O desenvolvimento de arquitetura software é suportado pela estrutura Robot Operating System (ROS). Finalmente, alguns testes experimentais são realizados para validar as soluções propostas e para avaliar o desempenho do sistema. Uma possível transferência de objetos é alcançada, mesmo que sejam necessários alguns refinamentos, melhorias e extensões para melhorar o desempenho e abrangência da solução

Nonverbal Communication During Human-Robot Object Handover. Improving Predictability of Humanoid Robots by Gaze and Gestures in Close Interaction

Meyer zu Borgsen S. Nonverbal Communication During Human-Robot Object Handover. Improving Predictability of Humanoid Robots by Gaze and Gestures in Close Interaction. Bielefeld: Universität Bielefeld; 2020.This doctoral thesis investigates the influence of nonverbal communication on human-robot object handover. Handing objects to one another is an everyday activity where two individuals cooperatively interact. Such close interactions incorporate a lot of nonverbal communication in order to create alignment in space and time. Understanding and transferring communication cues to robots becomes more and more important as e.g. service robots are expected to closely interact with humans in the near future. Their tasks often include delivering and taking objects. Thus, handover scenarios play an important role in human-robot interaction. A lot of work in this field of research focuses on speed, accuracy, and predictability of the robot’s movement during object handover. Still, robots need to be enabled to closely interact with naive users and not only experts. In this work I present how nonverbal communication can be implemented in robots to facilitate smooth handovers. I conducted a study on people with different levels of experience exchanging objects with a humanoid robot. It became clear that especially users with only little experience in regard to interaction with robots rely heavily on the communication cues they are used to on the basis of former interactions with humans. I added different gestures with the second arm, not directly involved in the transfer, to analyze the influence on synchronization, predictability, and human acceptance. Handing an object has a special movement trajectory itself which has not only the purpose of bringing the object or hand to the position of exchange but also of socially signalizing the intention to exchange an object. Another common type of nonverbal communication is gaze. It allows guessing the focus of attention of an interaction partner and thus helps to predict the next action. In order to evaluate handover interaction performance between human and robot, I applied the developed concepts to the humanoid robot Meka M1. By adding the humanoid robot head named Floka Head to the system, I created the Floka humanoid, to implement gaze strategies that aim to increase predictability and user comfort. This thesis contributes to the field of human-robot object handover by presenting study outcomes and concepts along with an implementation of improved software modules resulting in a fully functional object handing humanoid robot from perception and prediction capabilities to behaviors enhanced and improved by features of nonverbal communication

How to Communicate Robot Motion Intent: A Scoping Review

Robots are becoming increasingly omnipresent in our daily lives, supporting us and carrying out autonomous tasks. In Human-Robot Interaction, human actors benefit from understanding the robot's motion intent to avoid task failures and foster collaboration. Finding effective ways to communicate this intent to users has recently received increased research interest. However, no common language has been established to systematize robot motion intent. This work presents a scoping review aimed at unifying existing knowledge. Based on our analysis, we present an intent communication model that depicts the relationship between robot and human through different intent dimensions (intent type, intent information, intent location). We discuss these different intent dimensions and their interrelationships with different kinds of robots and human roles. Throughout our analysis, we classify the existing research literature along our intent communication model, allowing us to identify key patterns and possible directions for future research.Comment: Interactive Data Visualization of the Paper Corpus: https://rmi.robot-research.d

Joining teleoperation with robotics for advanced manipulation in hostile environments

Manipulators have been used for many years to perform remote handling tasks in hazardous environments. The development history of teleoperators is reviewed, and applications around the world are summarized. The effect of computer supervisory control is discussed, and similarities between robots and teleoperator research activities are delineated. With improved control strategies and system designs, combination of positive attributes of robots with teleoperators will lead to advanced machines capable of autonomy in unstructured environments. This concept of a telerobot is introduced as a goal for future activities