Modeling human-likeness in approaching motions of dual-arm autonomous robots

© 2018 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 worksThis paper addresses the problem of obtaining human-like motions with an anthropomorphic dual-arm torso assembled on a mobile platform. The focus is set on the coordinated movements of the robotic arms and the robot base while approaching a table to subsequently perform a bimanual manipulation task. For this, human movements are captured and mapped to the robot in order to compute the human dual-arm synergies. Since the demonstrated synergies change depending on the robot position, a recursive Cartesian-space discretization is presented based on these differences. Thereby, different movements of the arms are assigned to different regions of the Cartesian space. As an application example, a motion-planning algorithm exploiting this information is proposed and used.Postprint (published version

Human-like arm motion generation: a review

In the last decade, the objectives outlined by the needs of personal robotics have led to the rise of new biologically-inspired techniques for arm motion planning. This paper presents a literature review of the most recent research on the generation of human-like arm movements in humanoid and manipulation robotic systems. Search methods and inclusion criteria are described. The studies are analyzed taking into consideration the sources of publication, the experimental settings, the type of movements, the technical approach, and the human motor principles that have been used to inspire and assess human-likeness. Results show that there is a strong focus on the generation of single-arm reaching movements and biomimetic-based methods. However, there has been poor attention to manipulation, obstacle-avoidance mechanisms, and dual-arm motion generation. For these reasons, human-like arm motion generation may not fully respect human behavioral and neurological key features and may result restricted to specific tasks of human-robot interaction. Limitations and challenges are discussed to provide meaningful directions for future investigations.FCT Project UID/MAT/00013/2013FCT–Fundação para a Ciência e Tecnologia within the R&D Units Project Scope: UIDB/00319/2020

Compliant aerial manipulation.

The aerial manipulation is a research field which proposes the integration of robotic manipulators in aerial platforms, typically multirotors – widely known as “drones” – or autonomous helicopters. The development of this technology is motivated by the convenience to reduce the time, cost and risk associated to the execution of certain operations or tasks in high altitude areas or difficult access workspaces. Some illustrative application examples are the detection and insulation of leaks in pipe structures in chemical plants, repairing the corrosion in the blades of wind turbines, the maintenance of power lines, or the installation and retrieval of sensor devices in polluted areas. Although nowadays it is possible to find a wide variety of commercial multirotor platforms with payloads from a few gramps up to several kilograms, and flight times around thirty minutes, the development of an aerial manipulator is still a technological challenge due to the strong requirements relative to the design of the manipulator in terms of very low weight, low inertia, dexterity, mechanical robustness and control. The main contribution of this thesis is the design, development and experimental validation of several prototypes of lightweight (<2 kg) and compliant manipulators to be integrated in multirotor platforms, including human-size dual arm systems, compliant joint arms equipped with human-like finger modules for grasping, and long reach aerial manipulators. Since it is expected that the aerial manipulator is capable to execute inspection and maintenance tasks in a similar way a human operator would do, this thesis proposes a bioinspired design approach, trying to replicate the human arm in terms of size, kinematics, mass distribution, and compliance. This last feature is actually one of the key concepts developed and exploited in this work. Introducing a flexible element such as springs or elastomers between the servos and the links extends the capabilities of the manipulator, allowing the estimation and control of the torque/force, the detection of impacts and overloads, or the localization of obstacles by contact. It also improves safety and efficiency of the manipulator, especially during the operation on flight or in grabbing situations, where the impacts and contact forces may damage the manipulator or destabilize the aerial platform. Unlike most industrial manipulators, where force-torque control is possible at control rates above 1 kHz, the servo actuators typically employed in the development of aerial manipulators present important technological limitations: no torque feedback nor control, only position (and in some models, speed) references, low update rates (<100 Hz), and communication delays. However, these devices are still the best solution due to their high torque to weight ratio, low cost, compact design, and easy assembly and integration. In order to cope with these limitations, the compliant joint arms presented here estimate and control the wrenches from the deflection of the spring-lever transmission mechanism introduced in the joints, measured at joint level with encoders or potentiometers, or in the Cartesian space employing vision sensors. Note that in the developed prototypes, the maximum joint deflection is around 25 degrees, which corresponds to a deviation in the position of the end effector around 20 cm for a human-size arm. The capabilities and functionalities of the manipulators have been evaluated in fixed base test-bench firstly, and then in outdoor flight tests, integrating the arms in different commercial hexarotor platforms. Frequency characterization, position/force/impedance control, bimanual grasping, arm teleoperation, payload mass estimation, or contact-based obstacle localization are some of the experiments presented in this thesis that validate the developed prototypes.La manipulación aérea es un campo de investigación que propone la integración de manipuladores robóticos in plataformas aéreas, típicamente multirotores – comúnmente conocidos como “drones” – o helicópteros autónomos. El desarrollo de esta tecnología está motivada por la conveniencia de reducir el tiempo, coste y riesgo asociado a la ejecución de ciertas operaciones o tareas en áreas de gran altura o espacios de trabajo de difícil acceso. Algunos ejemplos ilustrativos de aplicaciones son la detección y aislamiento de fugas en estructura de tuberías en plantas químicas, la reparación de la corrosión en las palas de aerogeneradores, el mantenimiento de líneas eléctricas, o la instalación y recuperación de sensores en zonas contaminadas. Aunque hoy en día es posible encontrar una amplia variedad de plataformas multirotor comerciales con cargas de pago desde unos pocos gramos hasta varios kilogramos, y tiempo de vuelo entorno a treinta minutos, el desarrollo de los manipuladores aéreos es todavía un desafío tecnológico debido a los exigentes requisitos relativos al diseño del manipulador en términos de muy bajo peso, baja inercia, destreza, robustez mecánica y control. La contribución principal de esta tesis es el diseño, desarrollo y validación experimental de varios prototipos de manipuladores de bajo peso (<2 kg) con capacidad de acomodación (“compliant”) para su integración en plataformas aéreas multirotor, incluyendo sistemas bi-brazo de tamaño humano, brazos robóticos de articulaciones flexibles con dedos antropomórficos para agarre, y manipuladores aéreos de largo alcance. Puesto que se prevé que el manipulador aéreo sea capaz de ejecutar tareas de inspección y mantenimiento de forma similar a como lo haría un operador humano, esta tesis propone un enfoque de diseño bio-inspirado, tratando de replicar el brazo humano en cuanto a tamaño, cinemática, distribución de masas y flexibilidad. Esta característica es de hecho uno de los conceptos clave desarrollados y utilizados en este trabajo. Al introducir un elemento elástico como los muelles o elastómeros entre el los actuadores y los enlaces se aumenta las capacidades del manipulador, permitiendo la estimación y control de las fuerzas y pares, la detección de impactos y sobrecargas, o la localización de obstáculos por contacto. Además mejora la seguridad y eficiencia del manipulador, especialmente durante las operaciones en vuelo, donde los impactos y fuerzas de contacto pueden dañar el manipulador o desestabilizar la plataforma aérea. A diferencia de la mayoría de manipuladores industriales, donde el control de fuerzas y pares es posible a tasas por encima de 1 kHz, los servo motores típicamente utilizados en el desarrollo de manipuladores aéreos presentan importantes limitaciones tecnológicas: no hay realimentación ni control de torque, sólo admiten referencias de posición (o bien de velocidad), y presentan retrasos de comunicación. Sin embargo, estos dispositivos son todavía la mejor solución debido al alto ratio de torque a peso, por su bajo peso, diseño compacto y facilidad de ensamblado e integración. Para suplir estas limitaciones, los brazos robóticos flexibles presentados aquí permiten estimar y controlar las fuerzas a partir de la deflexión del mecanismo de muelle-palanca introducido en las articulaciones, medida a nivel articular mediante potenciómetros o codificadores, o en espacio Cartesiano mediante sensores de visión. Tómese como referencia que en los prototipos desarrollados la máxima deflexión articular es de unos 25 grados, lo que corresponde a una desviación de posición en torno a 20 cm en el efector final para un brazo de tamaño humano. Las capacidades y funcionalidades de estos manipuladores se han evaluado en base fija primero, y luego en vuelos en exteriores, integrando los brazos en diferentes plataformas hexartor comerciales. Caracterización frecuencial, control de posición/fuerza/impedancia, agarre bimanual, teleoperación de brazos, estimación de carga, o la localización de obstáculos mediante contacto son algunos de los experimentos presentados en esta tesis para validar los prototipos desarrollados por el auto

Control strategies for cleaning robots in domestic applications: A comprehensive review:

Service robots are built and developed for various applications to support humans as companion, caretaker, or domestic support. As the number of elderly people grows, service robots will be in increasing demand. Particularly, one of the main tasks performed by elderly people, and others, is the complex task of cleaning. Therefore, cleaning tasks, such as sweeping floors, washing dishes, and wiping windows, have been developed for the domestic environment using service robots or robot manipulators with several control approaches. This article is primarily focused on control methodology used for cleaning tasks. Specifically, this work mainly discusses classical control and learning-based controlled methods. The classical control approaches, which consist of position control, force control, and impedance control , are commonly used for cleaning purposes in a highly controlled environment. However, classical control methods cannot be generalized for cluttered environment so that learning-based control methods could be an alternative solution. Learning-based control methods for cleaning tasks can encompass three approaches: learning from demonstration (LfD), supervised learning (SL), and reinforcement learning (RL). These control approaches have their own capabilities to generalize the cleaning tasks in the new environment. For example, LfD, which many research groups have used for cleaning tasks, can generate complex cleaning trajectories based on human demonstration. Also, SL can support the prediction of dirt areas and cleaning motion using large number of data set. Finally, RL can learn cleaning actions and interact with the new environment by the robot itself. In this context, this article aims to provide a general overview of robotic cleaning tasks based on different types of control methods using manipulator. It also suggest a description of the future directions of cleaning tasks based on the evaluation of the control approaches

An Augmented Discrete-Time Approach for Human-Robot Collaboration

Human-robot collaboration (HRC) is a key feature to distinguish the new generation of robots from conventional robots. Relevant HRC topics have been extensively investigated recently in academic institutes and companies to improve human and robot interactive performance. Generally, human motor control regulates human motion adaptively to the external environment with safety, compliance, stability, and efficiency. Inspired by this, we propose an augmented approach to make a robot understand human motion behaviors based on human kinematics and human postural impedance adaptation. Human kinematics is identified by geometry kinematics approach to map human arm configuration as well as stiffness index controlled by hand gesture to anthropomorphic arm. While human arm postural stiffness is estimated and calibrated within robot empirical stability region, human motion is captured by employing a geometry vector approach based on Kinect. A biomimetic controller in discrete-time is employed to make Baxter robot arm imitate human arm behaviors based on Baxter robot dynamics. An object moving task is implemented to validate the performance of proposed methods based on Baxter robot simulator. Results show that the proposed approach to HRC is intuitive, stable, efficient, and compliant, which may have various applications in human-robot collaboration scenarios

Motion planning using synergies : application to anthropomorphic dual-arm robots

Motion planning is a traditional field in robotics, but new problems are nevertheless incessantly appearing, due to continuous advances in the robot developments. In order to solve these new problems, as well as to improve the existing solutions to classical problems, new approaches are being proposed. A paradigmatic case is the humanoid robotics, since the advances done in this field require motion planners not only to look efficiently for an optimal solution in the classic way, i.e. optimizing consumed energy or time in the plan execution, but also looking for human-like solutions, i.e. requiring the robot movements to be similar to those of the human beings. This anthropomorphism in the robot motion is desired not only for aesthetical reasons, but it is also needed to allow a better and safer human-robot collaboration: humans can predict more easily anthropomorphic robot motions thus avoiding collisions and enhancing the collaboration with the robot. Nevertheless, obtaining a satisfactory performance of these anthropomorphic robotic systems requires the automatic planning of the movements, which is still an arduous and non-evident task since the complexity of the planning problem increases exponentially with the number of degrees of freedom of the robotic system. This doctoral thesis tackles the problem of planning the motions of dual-arm anthropomorphic robots (optionally with mobile base). The main objective is twofold: obtaining robot motions both in an efficient and in a human-like fashion at the same time. Trying to mimic the human movements while reducing the complexity of the search space for planning purposes leads to the concept of synergies, which could be conceptually defined as correlations (in the joint configuration space as well as in the joint velocity space) between the degrees of freedom of the system. This work proposes new sampling-based motion-planning procedures that exploit the concept of synergies, both in the configuration and velocity space, coordinating the movements of the arms, the hands and the mobile base of mobile anthropomorphic dual-arm robots.La planificación de movimientos es un campo tradicional de la robótica, sin embargo aparecen incesantemente nuevos problemas debido a los continuos avances en el desarrollo de los robots. Para resolver esos nuevos problemas, así como para mejorar las soluciones existentes a los problemas clásicos, se están proponiendo nuevos enfoques. Un caso paradigmático es la robótica humanoide, ya que los avances realizados en este campo requieren que los algoritmos planificadores de movimientos no sólo encuentren eficientemente una solución óptima en el sentido clásico, es decir, optimizar el consumo de energía o el tiempo de ejecución de la trayectoria; sino que también busquen soluciones con apariencia humana, es decir, que el movimiento del robot sea similar al del ser humano. Este antropomorfismo en el movimiento del robot se busca no sólo por razones estéticas, sino porque también es necesario para permitir una colaboración mejor y más segura entre el robot y el operario: el ser humano puede predecir con mayor facilidad los movimientos del robot si éstos son antropomórficos, evitando así las colisiones y mejorando la colaboración humano robot. Sin embargo, para obtener un desempeño satisfactorio de estos sistemas robóticos antropomórficos se requiere una planificación automática de sus movimientos, lo que sigue siendo una tarea ardua y poco evidente, ya que la complejidad del problema aumenta exponencialmente con el número de grados de libertad del sistema robótico. Esta tesis doctoral aborda el problema de la planificación de movimientos en robots antropomorfos bibrazo (opcionalmente con base móvil). El objetivo aquí es doble: obtener movimientos robóticos de forma eficiente y, a la vez, que tengan apariencia humana. Intentar imitar los movimientos humanos mientras a la vez se reduce la complejidad del espacio de búsqueda conduce al concepto de sinergias, que podrían definirse conceptualmente como correlaciones (tanto en el espacio de configuraciones como en el espacio de velocidades de las articulaciones) entre los distintos grados de libertad del sistema. Este trabajo propone nuevos procedimientos de planificación de movimientos que explotan el concepto de sinergias, tanto en el espacio de configuraciones como en el espacio de velocidades, coordinando así los movimientos de los brazos, las manos y la base móvil de robots móviles, bibrazo y antropomórficos.Postprint (published version

DMPs-based skill learning for redundant dual-arm robotic synchronized cooperative manipulation

Dual-arm robot manipulation is applicable to many domains, such as industrial, medical, and home service scenes. Learning from demonstrations (LfD) is a highly effective paradigm for robotic learning, where a robot learns from human actions directly and can be used autonomously for new tasks, avoiding the complicated analytical calculation for motion programming. However, the learned skills are not easy to generalize to new cases where special constraints such as varying relative distance limitation of robotic end effectors for human-like cooperative manipulations exist. In this paper, we propose a dynamic movement primitives (DMPs) based skills learning framework for redundant dual-arm robots. The method, with a coupling acceleration term to the DMPs function, is inspired by the transient performance control of Barrier Lyapunov Functions (BLFs). The additional coupling acceleration term is calculated based on the constant joint distance and varying relative distance limitations of end effectors for object approaching actions. In addition, we integrate the generated actions in joint space and the solution for a redundant dual-arm robot to complete a human-like manipulation. Simulations undertaken in Matlab and Gazebo environments certify the effectiveness of the proposed method