The development of robot control programs is a complex task. Many robots are different in their electrical and mechanical structure which is also reflected in the software. Specific robot software environments support the program development, but are mainly text-based and usually applied by experts in the field with profound knowledge of the target robot. This paper presents a graphical programming environment which aims to ease the development of robot control programs. In contrast to existing graphical robot programming environments, our approach focuses on the composition of parallel action sequences. The developed environment allows to schedule independent robot actions on parallel execution lines and provides mechanism to avoid side-effects of parallel actions. The developed environment is platform-independent and based on the model-driven paradigm. The feasibility of our approach is shown by the application of the sequencer to a simulated service robot and a robot for educational purpose.
Robots are widespread across diverse application contexts. Teaching robots to perform tasks, in their respective contexts, demands a high domain and programming expertise. However, robot programming faces high entry barriers due to the complexity of robot programming itself. Even for experts robot programming is a cumbersome and error-prone task where faulty robot programs can be created, causing damage when being executed on a real robot. To simplify the process of robot programming, we combine Augmented Reality (AR) with principles of end-user development. By combining them, the real environ…
The control architecture of autonomous robots can be developed by programming and integrating multiple software components that individually control separate behaviors. This approach requires additional mechanisms to coordinate their concurrent execution. This paper presents a programming method for such components that has been designed to facilitate their coordinated execution. Each component is programmed as a module that controls a separate robot behavior together with a set of functions for execution management. The details of this proposal are formulated in the form of a ROS-based softwa…
Robot programming methods for industrial robots are time consuming and often require operators to have knowledge in robotics and programming. To reduce costs associated with reprogramming, various interfaces using augmented reality have recently been proposed to provide users with more intuitive means of controlling robots in real-time and programming them without having to code. However, most solutions require the operator to be close to the real robot's workspace which implies either removing it from the production line or shutting down the whole production line due to safety hazards. We pro…
As robots interact with a broader range of end-users, end-user robot programming has helped democratize robot programming by empowering end-users who may not have experience in robot programming to customize robots to meet their individual contextual needs. This article surveys work on end-user robot programming, with a focus on end-user program specification. It describes the primary domains, programming phases, and design choices represented by the end-user robot programming literature. The survey concludes by highlighting open directions for further investigation to enhance and widen the re…
Programming robots for general purpose applications is extremely challenging due to the great diversity of end-user tasks ranging from manufacturing environments to personal homes. Recent work has focused on enabling end-users to program robots using Programming by Demonstration. However, teaching robots new actions from scratch that can be reused for unseen tasks remains a difficult challenge and is generally left up to robotic experts. We propose iRoPro, an interactive Robot Programming framework that allows end-users to teach robots new actions from scratch and reuse them with a task planne…
In this paper, we report on our use of cloud-robotics solutions to teach a Robotics Applications Programming course at Zurich University of Applied Sciences (ZHAW). The usage of Kubernetes based cloud computing environment combined with real robots -- turtlebots and Niryo arms -- allowed us to: 1) minimize the set up times required to provide a Robotic Operating System (ROS) simulation and development environment to all students independently of their laptop architecture and OS; 2) provide a seamless "simulation to real" experience preserving the exciting experience of writing software interac…
University of Texas at Austin（德克萨斯大学奥斯汀分校）；University of Nebraska Omaha（内布拉斯加大学奥马哈分校）
Robot programming typically makes use of a set of mechanical skills that is acquired by machine learning. Because there is in general no guarantee that machine learning produces robot programs that are free of surprising behavior, the safe execution of a robot program must utilize monitoring modules that take sensor data as inputs in real time to ensure the correctness of the skill execution. Owing to the fact that sensors and monitoring algorithms are usually subject to physical restrictions and that effective robot programming is sensitive to the selection of skill parameters, these consider…
The recent availability of commercial-off-the-shelf (COTS) legged robot platforms have opened up new opportunities in deploying legged systems into different scenarios. While the main advantage of legged robots is their ability to traverse unstructured terrain, there are still large gaps between what robot platforms can achieve and their animal counterparts. Therefore, when deploying as part of a heterogeneous robot team of different platforms, it is beneficial to understand the different scenarios where a legged platform would perform better than a wheeled, tracked or aerial platform. Two COT…
We study optimal Multi-robot Path Planning (MPP) on graphs, in order to improve the efficiency of multi-robot system (MRS) in the warehouse-like environment. We propose a novel algorithm, OMRPP (One-way Multi-robot Path Planning) based on Integer programming (IP) method. We focus on reducing the cost caused by a set of robots moving from their initial configuration to goal configuration in the warehouse-like environment. The novelty of this work includes: (1) proposing a topological map extraction based on the property of warehouse-like environment to reduce the scale of constructed IP model; …
Interactive Robot Programming for Surface Finishing via Task-Centric Mixed Reality Interfaces
Institute of Robotics and Mechatronics, German Aerospace Center (DLR)（机器人与机电系统研究所，德国航空航天中心）；University of Lübeck（吕贝克大学）；Autonomous Systems Lab, Institute of Computer Technology, TU Wien（自主系统实验室，计算机技术研究所，维也纳技术大学）
Istituto Italiano di Tecnologia（意大利技术研究院）；Politecnico di Milano（米兰理工大学）
The recognition of actions performed by humans and the anticipation of their intentions are important enablers to yield sociable and successful collaboration in human-robot teams. Meanwhile, robots should have the capacity to deal with multiple objectives and constraints, arising from the collaborative task or the human. In this regard, we propose vision techniques to perform human action recognition and image classification, which are integrated into an Augmented Hierarchical Quadratic Programming (AHQP) scheme to hierarchically optimize the robot's reactive behavior and human ergonomics. The…
University of Coimbra（科英布拉大学）；Centre for Mechanical Engineering, Materials and Processes（机械工程、材料与工艺中心）
There is a great demand for the robotization of manufacturing processes fea-turing monotonous labor. Some manufacturing tasks requiring specific skills (welding, painting, etc.) suffer from a lack of workers. Robots have been used in these tasks, but their flexibility is limited since they are still difficult to program/re-program by non-experts, making them inaccessible to most companies. Robot offline programming (OLP) is reliable. However, generat-ed paths directly from CAD/CAM do not include relevant parameters repre-senting human skills such as robot end-effector orientations and velociti…
There is a growing need for computational tools to automatically design and verify autonomous systems, especially complex robotic systems involving perception, planning, control, and hardware in the autonomy stack. Differentiable programming has recently emerged as powerful tool for modeling and optimization. However, very few studies have been done to understand how differentiable programming can be used for robust, certifiable end-to-end design optimization. In this paper, we fill this gap by combining differentiable programming for robot design optimization with a novel statistical framewor…
CNRS-University of Montpellier（法国国家科学研究中心-蒙彼利埃大学）；CNRS-AIST Joint Robotics Laboratory（法国国家科学研究中心-产业技术综合研究所联合机器人实验室）
Bidirectional object handover between a human and a robot enables an important functionality skill in robotic human-centered manufacturing or services. The problem in achieving this skill lies in the capacity of any solution to deal with three important aspects: (i) synchronized timing for the handing over phases; (ii) the handling of object pose constraints; and (iii) understanding the haptic exchanging to seamlessly achieve some steps of the (i). We propose a new approach for (i) and (ii) consisting in explicitly formulating the handover process as constraints in a task-space quadratic progr…
Karlsruhe Institute of Technology（卡尔斯鲁厄理工学院）；Karlsruhe University of Applied Sciences（卡尔斯鲁厄应用科学大学）
Intuitive robot programming through use of tracked smart input devices relies on fixed, external tracking systems, most often employing infra-red markers. Such an approach is frequently combined with projector-based augmented reality for better visualisation and interface. The combined system, although providing an intuitive programming platform with short cycle times even for inexperienced users, is immobile, expensive and requires extensive calibration. When faced with a changing environment and large number of robots it becomes sorely impractical. Here we present our work on infra-red marke…
Roma Tre University（罗马第三大学）；University of Cassino and Southern Lazio（卡西诺与南拉齐奥大学）
In this work, we address a task allocation problem for human multi-robot settings. Given a set of tasks to perform, we formulate a general Mixed-Integer Linear Programming (MILP) problem aiming at minimizing the overall execution time while optimizing the quality of the executed tasks as well as human and robotic workload. Different skills of the agents, both human and robotic, are taken into account and human operators are enabled to either directly execute tasks or play supervisory roles; moreover, multiple manipulators can tightly collaborate if required to carry out a task. Finally, as rea…
HeROS: a miniaturised platform for research and development on Heterogeneous RObotic Systems
Warsaw University of Technology（华沙理工大学）；Faculty of Electronics and Information Technology（电子与信息技术学院）；Institute of Control and Computation Engineering（控制与计算工程研究所）
University of Stuttgart（斯图加特大学）；Max Planck Institute for Intelligent Systems（马克斯·普朗克智能系统研究所）；Technische Universität Berlin（柏林工业大学）
In this paper, we tackle the problem of human-robot coordination in sequences of manipulation tasks. Our approach integrates hierarchical human motion prediction with Task and Motion Planning (TAMP). We first devise a hierarchical motion prediction approach by combining Inverse Reinforcement Learning and short-term motion prediction using a Recurrent Neural Network. In a second step, we propose a dynamic version of the TAMP algorithm Logic-Geometric Programming (LGP). Our version of Dynamic LGP, replans periodically to handle the mismatch between the human motion prediction and the actual huma…
Recent years have seen a growth in the number of industrial robots working closely with end-users such as factory workers. This growing use of collaborative robots has been enabled in part due to the availability of end-user robot programming methods that allow users who are not robot programmers to teach robots task actions. Programming by Demonstration (PbD) is one such end-user programming method that enables users to bypass the complexities of specifying robot motions using programming languages by instead demonstrating the desired robot behavior. Demonstrations are often provided by physi…
CSIRO（澳大利亚联邦科学与工业研究组织）；University of Moratuwa（莫拉图瓦大学）
Autonomous navigation systems based on computer vision sensors often require sophisticated robotics platforms which are very expensive. This poses a barrier for the implementation and testing of complex localization, mapping, and navigation algorithms that are vital in robotics applications. Addressing this issue, in this work, Robot Operating System (ROS) supported mobile robotics platforms are compared and an end-to-end implementation of an autonomous navigation system based on a low-cost educational robotics platform, AlphaBot2 is presented, while integrating the Intel RealSense D435 camera…
Nowadays, design and development of legged quadruped robots is a quite active area of scientific research. In fact, the legged robots have become popular due to their capabilities to adapt to harsh terrains and diverse environmental conditions in comparison to other mobile robots. With the higher demand for legged robot experiments, more researches and engineers need an affordable and quick way of locomotion algorithm development. In this paper, we present a new open source quadruped robot HyperDog platform, which features 12 RC servo motors, onboard NVIDIA Jetson nano computer and STM32F4 Dis…
CoBT: Collaborative Programming of Behaviour Trees from One Demonstration for Robot Manipulation
Technological University Dublin（都柏林理工大学）；Irish Manufacturing Research（爱尔兰制造研究院）；Atlantic Technological University（大西洋理工大学）；University of Modena and Reggio Emilia（摩德纳-雷焦艾米利亚大学）；Trinity College Dublin（都柏林圣三一大学）；ADAPT Research Centre（ADAPT研究中心）
