Computational Foundations for Safe and Efficient Human-Robot Collaboration in Assembly Cells

Human and robots have complementary strengths in performing assembly operations. Humans are very good at perception tasks in unstructured environments. They are able to recognize and locate a part from a box of miscellaneous parts. They are also very good at complex manipulation in tight spaces. The sensory characteristics of the humans, motor abilities, knowledge and skills give the humans the ability to react to unexpected situations and resolve problems quickly. In contrast, robots are very good at pick and place operations and highly repeatable in placement tasks. Robots can perform tasks at high speeds and still maintain precision in their operations. Robots can also operate for long periods of times. Robots are also very good at applying high forces and torques. Typically, robots are used in mass production. Small batch and custom production operations predominantly use manual labor. The high labor cost is making it difficult for small and medium manufacturers to remain cost competitive in high wage markets. These manufactures are mainly involved in small batch and custom production. They need to find a way to reduce the labor cost in assembly operations. Purely robotic cells will not be able to provide them the necessary flexibility. Creating hybrid cells where humans and robots can collaborate in close physical proximities is a potential solution. The underlying idea behind such cells is to decompose assembly operations into tasks such that humans and robots can collaborate by performing sub-tasks that are suitable for them. Realizing hybrid cells that enable effective human and robot collaboration is challenging. This dissertation addresses the following three computational issues involved in developing and utilizing hybrid assembly cells: - We should be able to automatically generate plans to operate hybrid assembly cells to ensure efficient cell operation. This requires generating feasible assembly sequences and instructions for robots and human operators, respectively. Automated planning poses the following two challenges. First, generating operation plans for complex assemblies is challenging. The complexity can come due to the combinatorial explosion caused by the size of the assembly or the complex paths needed to perform the assembly. Second, generating feasible plans requires accounting for robot and human motion constraints. The first objective of the dissertation is to develop the underlying computational foundations for automatically generating plans for the operation of hybrid cells. It addresses both assembly complexity and motion constraints issues. - The collaboration between humans and robots in the assembly cell will only be practical if human safety can be ensured during the assembly tasks that require collaboration between humans and robots. The second objective of the dissertation is to evaluate different options for real-time monitoring of the state of human operator with respect to the robot and develop strategies for taking appropriate measures to ensure human safety when the planned move by the robot may compromise the safety of the human operator. In order to be competitive in the market, the developed solution will have to include considerations about cost without significantly compromising quality. - In the envisioned hybrid cell, we will be relying on human operators to bring the part into the cell. If the human operator makes an error in selecting the part or fails to place it correctly, the robot will be unable to correctly perform the task assigned to it. If the error goes undetected, it can lead to a defective product and inefficiencies in the cell operation. The reason for human error can be either confusion due to poor quality instructions or human operator not paying adequate attention to the instructions. In order to ensure smooth and error-free operation of the cell, we will need to monitor the state of the assembly operations in the cell. The third objective of the dissertation is to identify and track parts in the cell and automatically generate instructions for taking corrective actions if a human operator deviates from the selected plan. Potential corrective actions may involve re-planning if it is possible to continue assembly from the current state. Corrective actions may also involve issuing warning and generating instructions to undo the current task.

Vision-Based Solutions for Human-Robot Collaboration in Industrial Workcells

Industrial robots are both versatile and high performant, enabling the flexible automation typical of the modern Smart Factories. For safety reasons, however, they must be relegated inside closed fences and/or virtual safety barriers, to keep them strictly separated from human operators. This can be a limitation in some scenarios in which it is useful to combine the human cognitive skill with the accuracy and repeatability of a robot, or simply to allow a safe coexistence in a shared workspace. Collaborative robots (cobots), on the other hand, are intrinsically limited in speed and power in order to share workspace and tasks with human operators, and feature the very intuitive hand guiding programming method. Cobots, however, cannot compete with industrial robots in terms of performance, and are thus useful only in a limited niche, where they can actually bring an improvement in productivity and/or in the quality of the work thanks to their synergy with human operators. The limitations of both the pure industrial and the collaborative paradigms can be overcome by combining industrial robots with artificial vision. In particular, vision can be exploited for a real-time adjustment of the pre-programmed task-based robot trajectory, by means of the visual tracking of dynamic obstacles (e.g. human operators). This strategy allows the robot to modify its motion only when necessary, thus maintain a high level of productivity but at the same time increasing its versatility. Other than that, vision offers the possibility of more intuitive programming paradigms for the industrial robots as well, such as the programming by demonstration paradigm. These possibilities offered by artificial vision enable, as a matter of fact, an efficacious and promising way of achieving human-robot collaboration, which has the advantage of overcoming the limitations of both the previous paradigms yet keeping their strengths.

Preventing worker’s musculoskeletal disorders with wearable inertial sensors: ergonomics and modelling of physical human-robot interactions

The most widespread work-related diseases are musculoskeletal disorders (MSD) caused by awkward postures and excessive effort to upper limb muscles during work operations. The use of wearable IMU sensors could monitor the workers constantly to prevent hazardous actions, thus diminishing work injuries. In this thesis, procedures are developed and tested for ergonomic analyses in a working environment, based on a commercial motion capture system (MoCap) made of 17 Inertial Measurement Units (IMUs). An IMU is usually made of a tri-axial gyroscope, a tri-axial accelerometer, and a tri-axial magnetometer that, through sensor fusion algorithms, estimates its attitude. Effective strategies for preventing MSD rely on various aspects: firstly, the accuracy of the IMU, depending on the chosen sensor and its calibration; secondly, the correct identification of the pose of each sensor on the worker’s body; thirdly, the chosen multibody model, which must consider both the accuracy and the computational burden, to provide results in real-time; finally, the model scaling law, which defines the possibility of a fast and accurate personalization of the multibody model geometry. Moreover, the MSD can be diminished using collaborative robots (cobots) as assisted devices for complex or heavy operations to relieve the worker's effort during repetitive tasks. All these aspects are considered to test and show the efficiency and usability of inertial MoCap systems for assessing ergonomics evaluation in real-time and implementing safety control strategies in collaborative robotics. Validation is performed with several experimental tests, both to test the proposed procedures and to compare the results of real-time multibody models developed in this thesis with the results from commercial software. As an additional result, the positive effects of using cobots as assisted devices for reducing human effort in repetitive industrial tasks are also shown, to demonstrate the potential of wearable electronics in on-field ergonomics analyses for industrial applications.

Dynamic Human Robot Interaction Framework Using Deep Learning and Robot Operating System (ROS): a practical approach

Trying to explain to a robot what to do is a difficult undertaking, and only specific types of people have been able to do so far, such as programmers or operators who have learned how to use controllers to communicate with a robot. My internship's goal was to create and develop a framework that would make that easier. The system uses deep learning techniques to recognize a set of hand gestures, both static and dynamic. Then, based on the gesture, it sends a command to a robot. To be as generic as feasible, the communication is implemented using Robot Operating System (ROS). Furthermore, users can add new recognizable gestures and link them to new robot actions; a finite state automaton enforces the users' input verification and correct action sequence. Finally, the users can create and utilize a macro to describe a sequence of actions performable by a robot.

Robotics and neurodevelopmental disorder: design and implementation of a system of engagement metrics in human-robot interactions.

In the recent decades, robotics has become firmly embedded in areas such as education, teaching, medicine, psychology and many others. We focus here on social robotics; social robots are designed to interact with people in a natural and interpersonal way, often to achieve positive results in different applications. To interact and cooperate with humans in their daily-life activities, robots should exhibit human-like intelligence. The rapid expansion of social robotics and the existence of various kinds of robots on the market have allowed research groups to carry out multiple experiments. The experiments carried out have led to the collections of various kinds of data, which can be used or processed for psychological studies, and studies in other fields. However, there are no tools available in which data can be stored, processed and shared with other research groups. This thesis proposes the design and implementation of visual tool for organizing dataflows in Human Robot Interaction (HRI).

DSAAR: distributed software architecture for autonomous robots

Dissertação apresentada na Faculdade de Ciências e Tecnologia da Universidade Nova de Lisboa para obtenção do grau de Mestre em Engenharia Electrotécnica

RGBD Human-Hand recognition for the Interaction with Robot-Hand

New low cost sensors and the new open free libraries for 3D image processing are permitting to achieve important advances for robot vision applications such as tridimensional object recognition, semantic mapping, navigation and localization of robots, human detection and/or gesture recognition for human-machine interaction. In this paper, a method to recognize the human hand and to track the fingers is proposed. This new method is based on point clouds from range images, RGBD. It does not require visual marks, camera calibration, environment knowledge and complex expensive acquisition systems. Furthermore, this method has been implemented to create a human interface in order to move a robot hand. The human hand is recognized and the movement of the fingers is analyzed. Afterwards, it is imitated from a Barret hand, using communication events programmed from ROS.

Towards Human-like Bimanual Movements in Anthropomorphic Robots: A Nonlinear Optimization Approach

Previously we have presented a model for generating human-like arm and hand movements on an unimanual anthropomorphic robot involved in human-robot collaboration tasks. The present paper aims to extend our model in order to address the generation of human-like bimanual movement sequences which are challenged by scenarios cluttered with obstacles. Movement planning involves large scale nonlinear constrained optimization problems which are solved using the IPOPT solver. Simulation studies show that the model generates feasible and realistic hand trajectories for action sequences involving the two hands. The computational costs involved in the planning allow for real-time human robot-interaction. A qualitative analysis reveals that the movements of the robot exhibit basic characteristics of human movements.

Nonlinear optimization for human-like synchronous movements of a dual arm-hand robotic system

In previous work we have presented a model capable of generating human-like movements for a dual arm-hand robot involved in human-robot cooperative tasks. However, the focus was on the generation of reach-to-grasp and reach-to-regrasp bimanual movements and no synchrony in timing was taken into account. In this paper we extend the previous model in order to accomplish bimanual manipulation tasks by synchronously moving both arms and hands of an anthropomorphic robotic system. Specifically, the new extended model has been designed for two different tasks with different degrees of difficulty. Numerical results were obtained by the implementation of the IPOPT solver embedded in our MATLAB simulator.

Towards human-like bimanual movements in anthropomorphic robots: a nonlinear optimization approach

Previously we have presented a model for generating human-like arm and hand movements on an unimanual anthropomorphic robot involved in human-robot collaboration tasks. The present paper aims to extend our model in order to address the generation of human-like bimanual movement sequences which are challenged by scenarios cluttered with obstacles. Movement planning involves large scale nonlinear constrained optimization problems which are solved using the IPOPT solver. Simulation studies show that the model generates feasible and realistic hand trajectories for action sequences involving the two hands. The computational costs involved in the planning allow for real-time human robot-interaction. A qualitative analysis reveals that the movements of the robot exhibit basic characteristics of human movements.

Intelligent task-level grasp mapping for robot control

In the future, robots will enter our everyday lives to help us with various tasks.For a complete integration and cooperation with humans, these robots needto be able to acquire new skills. Sensor capabilities for navigation in real humanenvironments and intelligent interaction with humans are some of the keychallenges.Learning by demonstration systems focus on the problem of human robotinteraction, and let the human teach the robot by demonstrating the task usinghis own hands. In this thesis, we present a solution to a subproblem within thelearning by demonstration field, namely human-robot grasp mapping. Robotgrasping of objects in a home or office environment is challenging problem.Programming by demonstration systems, can give important skills for aidingthe robot in the grasping task.The thesis presents two techniques for human-robot grasp mapping, directrobot imitation from human demonstrator and intelligent grasp imitation. Inintelligent grasp mapping, the robot takes the size and shape of the object intoconsideration, while for direct mapping, only the pose of the human hand isavailable.These are evaluated in a simulated environment on several robot platforms.The results show that knowing the object shape and size for a grasping taskimproves the robot precision and performance

Optimization-Based Robotic Manipulation for Safe Interaction with Human Operators

This thesis investigates a method for human-robot interaction (HRI) in order to uphold productivity of industrial robots like minimization of the shortest operation time, while ensuring human safety like collision avoidance. For solving such problems an online motion planning approach for robotic manipulators with HRI has been proposed. The approach is based on model predictive control (MPC) with embedded mixed integer programming. The planning strategies of the robotic manipulators mainly considered in the thesis are directly performed in the workspace for easy obstacle representation. The non-convex optimization problem is approximated by a mixed-integer program (MIP). It is further effectively reformulated such that the number of binary variables and the number of feasible integer solutions are drastically decreased. Safety-relevant regions, which are potentially occupied by the human operators, can be generated online by a proposed method based on hidden Markov models. In contrast to previous approaches, which derive predictions based on probability density functions in the form of single points, such as most likely or expected human positions, the proposed method computes safety-relevant subsets of the workspace as a region which is possibly occupied by the human at future instances of time. The method is further enhanced by combining reachability analysis to increase the prediction accuracy. These safety-relevant regions can subsequently serve as safety constraints when the motion is planned by optimization. This way one arrives at motion plans that are safe, i.e. plans that avoid collision with a probability not less than a predefined threshold. The developed methods have been successfully applied to a developed demonstrator, where an industrial robot works in the same space as a human operator. The task of the industrial robot is to drive its end-effector according to a nominal sequence of grippingmotion-releasing operations while no collision with a human arm occurs.

Heterogeneous Multi-Robot Cooperation

This report addresses the problem of achieving cooperation within small- to medium- sized teams of heterogeneous mobile robots. I describe a software architecture I have developed, called ALLIANCE, that facilitates robust, fault tolerant, reliable, and adaptive cooperative control. In addition, an extended version of ALLIANCE, called L-ALLIANCE, is described, which incorporates a dynamic parameter update mechanism that allows teams of mobile robots to improve the efficiency of their mission performance through learning. A number of experimental results of implementing these architectures on both physical and simulated mobile robot teams are described. In addition, this report presents the results of studies of a number of issues in mobile robot cooperation, including fault tolerant cooperative control, adaptive action selection, distributed control, robot awareness of team member actions, improving efficiency through learning, inter-robot communication, action recognition, and local versus global control.

Control of human behavior, mental processes and consciousness : essays in honor of the 60th birthday of August Flammer

In this book, an international group of leading scientists present perspectives on the control of human behavior, awareness, consciousness, and the meaning and function of perceived control or self-efficacy in people's lives. The book breaks down the barriers between subdisciplines, and thus constitutes an occasion to reflect on various facets of control in human life. Each expert reviews his or her field through the lens of perceived control and shows how these insights can be applied in practice.

Desarrollo de tecnologías de telemanipulación con alto grado de escalado orientadas a la interacción hombre-robot en entornos nucleares

Esta tesis se centra en desarrollo de tecnologías para la interacción hombre-robot en entornos nucleares de fusión. La problemática principal del sector de fusión nuclear radica en las condiciones ambientales tan extremas que hay en el interior del reactor, y la necesidad de que los equipos cumplan requisitos muy restrictivos para poder aguantar esos niveles de radiación, magnetismo, ultravacío, temperatura... Como no es viable la ejecución de tareas directamente por parte de humanos, habrá que utilizar dispositivos de manipulación remota para llevar a cabo los procesos de operación y mantenimiento. En las instalaciones de ITER es obligatorio tener un entorno controlado de extrema seguridad, que necesita de estándares validados. La definición y uso de protocolos es indispensable para regir su buen funcionamiento. Si nos centramos en la telemanipulación con algo grado de escalado, surge la necesidad de definir protocolos para sistemas abiertos que permitan la interacción entre equipos y dispositivos de diversa índole. En este contexto se plantea la definición del Protocolo de Teleoperación que permita la interconexión entre dispositivos maestros y esclavos de distinta tipología, pudiéndose comunicar bilateralmente entre sí y utilizar distintos algoritmos de control según la tarea a desempeñar. Este protocolo y su interconectividad se han puesto a prueba en la Plataforma Abierta de Teleoperación (P.A.T.) que se ha desarrollado e integrado en la ETSII UPM como una herramienta que permita probar, validar y realizar experimentos de telerrobótica. Actualmente, este Protocolo de Teleoperación se ha propuesto a través de AENOR al grupo ISO de Telerobotics como una solución válida al problema existente y se encuentra bajo revisión. Con el diseño de dicho protocolo se ha conseguido enlazar maestro y esclavo, sin embargo con los niveles de radiación tan altos que hay en ITER la electrónica del controlador no puede entrar dentro del tokamak. Por ello se propone que a través de una mínima electrónica convenientemente protegida se puedan multiplexar las señales de control que van a través del cableado umbilical desde el controlador hasta la base del robot. En este ejercicio teórico se demuestra la utilidad y viabilidad de utilizar este tipo de solución para reducir el volumen y peso del cableado umbilical en cifras aproximadas de un 90%, para ello hay que desarrollar una electrónica específica y con certificación RadHard para soportar los enormes niveles de radiación de ITER. Para este manipulador de tipo genérico y con ayuda de la Plataforma Abierta de Teleoperación, se ha desarrollado un algoritmo que mediante un sensor de fuerza/par y una IMU colocados en la muñeca del robot, y convenientemente protegidos ante la radiación, permiten calcular las fuerzas e inercias que produce la carga, esto es necesario para poder transmitirle al operador unas fuerzas escaladas, y que pueda sentir la carga que manipula, y no otras fuerzas que puedan influir en el esclavo remoto, como ocurre con otras técnicas de estimación de fuerzas. Como el blindaje de los sensores no debe ser grande ni pesado, habrá que destinar este tipo de tecnología a las tareas de mantenimiento de las paradas programadas de ITER, que es cuando los niveles de radiación están en sus valores mínimos. Por otro lado para que el operador sienta lo más fielmente posible la fuerza de carga se ha desarrollado una electrónica que mediante el control en corriente de los motores permita realizar un control en fuerza a partir de la caracterización de los motores del maestro. Además para aumentar la percepción del operador se han realizado unos experimentos que demuestran que al aplicar estímulos multimodales (visuales, auditivos y hápticos) aumenta su inmersión y el rendimiento en la consecución de la tarea puesto que influyen directamente en su capacidad de respuesta. Finalmente, y en referencia a la realimentación visual del operador, en ITER se trabaja con cámaras situadas en localizaciones estratégicas, si bien el humano cuando manipula objetos hace uso de su visión binocular cambiando constantemente el punto de vista adecuándose a las necesidades visuales de cada momento durante el desarrollo de la tarea. Por ello, se ha realizado una reconstrucción tridimensional del espacio de la tarea a partir de una cámara-sensor RGB-D, lo cual nos permite obtener un punto de vista binocular virtual móvil a partir de una cámara situada en un punto fijo que se puede proyectar en un dispositivo de visualización 3D para que el operador pueda variar el punto de vista estereoscópico según sus preferencias. La correcta integración de estas tecnologías para la interacción hombre-robot en la P.A.T. ha permitido validar mediante pruebas y experimentos para verificar su utilidad en la aplicación práctica de la telemanipulación con alto grado de escalado en entornos nucleares de fusión. Abstract This thesis focuses on developing technologies for human-robot interaction in nuclear fusion environments. The main problem of nuclear fusion sector resides in such extreme environmental conditions existing in the hot-cell, leading to very restrictive requirements for equipment in order to deal with these high levels of radiation, magnetism, ultravacuum, temperature... Since it is not feasible to carry out tasks directly by humans, we must use remote handling devices for accomplishing operation and maintenance processes. In ITER facilities it is mandatory to have a controlled environment of extreme safety and security with validated standards. The definition and use of protocols is essential to govern its operation. Focusing on Remote Handling with some degree of escalation, protocols must be defined for open systems to allow interaction among different kind of equipment and several multifunctional devices. In this context, a Teleoperation Protocol definition enables interconnection between master and slave devices from different typologies, being able to communicate bilaterally one each other and using different control algorithms depending on the task to perform. This protocol and its interconnectivity have been tested in the Teleoperation Open Platform (T.O.P.) that has been developed and integrated in the ETSII UPM as a tool to test, validate and conduct experiments in Telerobotics. Currently, this protocol has been proposed for Teleoperation through AENOR to the ISO Telerobotics group as a valid solution to the existing problem, and it is under review. Master and slave connection has been achieved with this protocol design, however with such high radiation levels in ITER, the controller electronics cannot enter inside the tokamak. Therefore it is proposed a multiplexed electronic board, that through suitable and RadHard protection processes, to transmit control signals through an umbilical cable from the controller to the robot base. In this theoretical exercise the utility and feasibility of using this type of solution reduce the volume and weight of the umbilical wiring approximate 90% less, although it is necessary to develop specific electronic hardware and validate in RadHard qualifications in order to handle huge levels of ITER radiation. Using generic manipulators does not allow to implement regular sensors for force feedback in ITER conditions. In this line of research, an algorithm to calculate the forces and inertia produced by the load has been developed using a force/torque sensor and IMU, both conveniently protected against radiation and placed on the robot wrist. Scaled forces should be transmitted to the operator, feeling load forces but not other undesirable forces in slave system as those resulting from other force estimation techniques. Since shielding of the sensors should not be large and heavy, it will be necessary to allocate this type of technology for programmed maintenance periods of ITER, when radiation levels are at their lowest levels. Moreover, the operator perception needs to feel load forces as accurate as possible, so some current control electronics were developed to perform a force control of master joint motors going through a correct motor characterization. In addition to increase the perception of the operator, some experiments were conducted to demonstrate applying multimodal stimuli (visual, auditory and haptic) increases immersion and performance in achieving the task since it is directly correlated with response time. Finally, referring to the visual feedback to the operator in ITER, it is usual to work with 2D cameras in strategic locations, while humans use binocular vision in direct object manipulation, constantly changing the point of view adapting it to the visual needs for performing manipulation during task procedures. In this line a three-dimensional reconstruction of non-structured scenarios has been developed using RGB-D sensor instead of cameras in the remote environment. Thus a mobile virtual binocular point of view could be generated from a camera at a fixed point, projecting stereoscopic images in 3D display device according to operator preferences. The successful integration of these technologies for human-robot interaction in the T.O.P., and validating them through tests and experiments, verify its usefulness in practical application of high scaling remote handling at nuclear fusion environments.