Reactive Collision Avoidance Strategies for Robots in direct Human-Robot Interaction

In the near future robots are sought to become an integral part of human everyday life. Also in industrial settings robotic Co-Workers are expected to become a commodity. Even though the particular application areas may vastly change, a robot always needs to act in a dynamic and partially unknown environment. It shall reactively generate motions and prevent upcoming collisions. If contact is desired or inevitable, it has to handle it robustly and safely. In order to evaluate existing algorithms an extensive simulation environment with test scenarios of rising complexity in 2D, 3D, and 6D was developed. After an initial analysis in rather complex 2D simulations, particularly well suited ones were extended to 3D as well as 6D, and combined into a hybrid strategy. Finally, the 6D MATLAB/Simulink/StateFlow implementation of a hybrid Circular & Potential Fields approach is used to perform the experimental analysis for static multi-object parcours and to avoid dynamically moving humans in a 6D task motion. Furthermore, we developed and tested a high-performance algorithm for tactile exploration of complex planar 3D wire elements, whose structure is a-priori unknown

Design, Execution, and Postmortem Analysis of Prolonged Autonomous Robot Operations

In the context of space missions and terrestrial applications, both mission goals and task implementations for autonomous robots are becoming increasingly complex. Thus, the challenge of monitoring the achievement of task objectives and checking the correctness of their implementation is becoming more and more difficult. To tackle these problems, we propose an unified architecture that supports different stakeholders during the different phases of the deployment: 1) the design phase; 2) the runtime phase; 3) the post-mortem analysis phase. Furthermore, we implement this architecture by enhancing our task programming framework RAFCON with powerful logging, debugging and profiling capabilities. We demonstrate the efficiency of our approach in the context of the ROBEX mission, during which the DLR Lightweight Rover Unit autonomously deployed several seismometers in an unknown rough terrain on Mt. Etna, Sicily. The analysis results for a state machine consisting of more than 1500 states and more than 1900 transitions are presented. Finally, we give a comparison between our framework and related software tools

Reactive Motion Generation for Robots in Dynamic Environments

In the near future robots are sought to become an integral part of human everyday life. Also in industrial settings robotic Co-Workers are expected to become a commodity. Even though the particular application areas may vastly change, a robot always needs to act in a dynamic and partially unknown environment. It shall reactively generate motions and prevent upcoming collisions. If contact is desired or inevitable, it has to handle it robustly and safely. For preventing collisions in a real-time fashion the Circular Fields method is a powerful scheme, which we developed further and evaluated it extensively. After an initial analysis in rather complex 2D simulations, we extend the evaluation to 3D as well as 6D, where we introduce a hybrid strategy based on Circular and Potential Fields. Finally, the 6D implementation of a hybrid Circular & Potential Fields approach is used to perform the experimental analysis for static multi-object parcours and to avoid a dynamically moving human in a 6D task motion. Based on the algorithms for collision avoidance we also develop and experimentally verify an algorithm for tactile exploration of complex planar 3D wire elements, whose structure is a-priori unknown

Safe Acting and Manipulation in Human Environments: A Key Concept for Robots in our Society

In this paper we review our work on safe acting and manipulation in human environments. In order for a robot to be able to safely interact with its environment it is primary to be able to react to unforeseen events in real-time on basically all levels of abstraction. Having this goal in mind, our contributions reach from fundamental understanding of human injury due to robot-human collisions as the underlying metric for “safe” behavior, various interaction control schemes that ground on the basic components impedance control and collision behavior, to real-time motion planning and behavior based control as an interface level for task planning. A significant amount of this work has found found its way into international standardization committees, products, and was applied in numerous real-world applications

A Visible‐Light‐Powered Polymerization Method for the Immobilization of Enantioselective Organocatalysts into Microreactors

A versatile one-step photopolymerization approach for the immobilization of enantioselective organocatalysts is presented. Chiral organocatalyst-containing monoliths based on polystyrene divinylbenzene copolymer were generated inside channels of microfluidic chips. Exemplary performance tests were performed for the monolithic Hayashi–Jørgensen catalyst in continuous flow, which showed good results for the Michael addition of aldehydes to nitroalkenes in terms of stereoselectivity and catalyst stability with minimal consumption of reagents and solvents

Collision Avoidance with Potential Fields Based on Parallel Processing of 3D-Point Cloud Data on the GPU

In this paper we present an experimental study on real-time collision avoidance with potential fields that are based on 3D point cloud data and processed on the Graphics Processing Unit (GPU). The virtual forces from the potential fields serve two purposes. First, they are used for changing the reference trajectory. Second they are projected to and applied on torque control level for generating according nullspace behavior together with a Cartesian impedance main control loop. The GPU algorithm creates a map representation that is quickly accessible. In addition, outliers and the robot structure are efficiently removed from the data, and the resolution of the representation can be easily adjusted. Based on the 3D robot representation and the remaining 3D environment data, the virtual forces that are fed to the trajectory plan- ning and torque controller are calculated. The algorithm is experimentally verified with a 7-Degree of Freedom (DoF) torque controlled KUKA/DLR Lightweight Robot for static and dynamic environmental conditions. To the authors knowledge, this is the first time that collision avoidance is demonstrated in real-time on a real robot using parallel GPU processing

RAFCON: A Graphical Tool for Engineering Complex, Robotic Tasks

Abstract— Robotic tasks are becoming increasingly complex, and with this also the robotic systems. This requires new tools to manage this complexity and to orchestrate the systems to fulfill demanding autonomous tasks. For this purpose, we developed a new graphical tool targeting at the creation and execution of robotic tasks, called RAFCON. These tasks are described in hierarchical state machines supporting concurrency. A formal notation of this concept is given. The tool provides many debugging mechanisms and a GUI with a graphical editor, allowing for intuitive visual programming and fast prototyping. The application of RAFCON for an autonomous mobile robot in the SpaceBotCamp competition has already proved to be successful

AN INTEGRATED CHIP-APPROACH TO STUDY ENANTIOSELECTIVE HETEROGENEOUS CATALYSTS AT THE MICROSCALE

In this work, we present novel approaches to study stereoselective catalytic processes at an unrivalled small scale. This is achieved by seamless on-chip integration of micro-sized chemical reactors and high performance liquid chromatography (HPLC)-columns on a single device. In contrast to our previous work, we present advanced chip-layouts and adapted strategies to transfer effluent samples from the reactor to the integrated HPLC column while keeping the flow through the reactor constant. This newly presented fluidic setup allows for the operation of several packed bed reactors combined with chip-based HPLC and mass spectrometric (MS) detection enabling the investigations of newly designed catalysts

Investigating the Influence of Haptic Feedback in Rover Navigation with Communication Delay

Safe navigation on rough terrain in the presence of unforeseen obstacles is an indispensable element of many robotic applications. In such conditions, autonomous navigation is often not a viable option within certain safety margins. Yet, a human-in-the-loop can also be arduous to include in the system, especially in scenarios where a communication delay is present. Haptic force feedback has been shown to provide benefits in rover navigation, also when confronted with higher communication delays. Therefore, in this paper we present the results of a user study comparing various performance metrics when controlling a rover with a car-like interface with and without fictitious force feedback, both with no communication delay and with a delay of 800 ms. The results indicate that with force feedback the navigation is slower, but task performance in the proximity of obstacles is improved

Robotic Agents Capable of Natural and Safe Physical Interaction with Human Co-Workers

Many future application scenarios of robotics envision robotic agents to be in close physical interaction with humans: On the factory floor, robotic agents shall support their human co-workers with the dull and health threatening parts of their jobs. In their homes, robotic agents shall enable people to stay independent, even if they have disabilities that require physical help in their daily life – a pressing need for our aging societies. A key requirement for such robotic agents is that they are safety-aware, that is, that they know when actions may hurt or threaten humans and actively refrain from performing them. Safe robot control systems are a current research focus in control theory. The control system designs, however, are a bit paranoid: programmers build “software fences” around people, effectively preventing physical interactions. To physically interact in a competent manner robotic agents have to reason about the task context, the human, and her intentions. In this paper, we propose to extend cognition-enabled robot control by introducing humans, physical interaction events, and safe movements as first class objects into the plan language. We show the power of the safety-aware control approach in a real-world scenario with a leading-edge autonomous manipulation platform. Finally, we share our experimental recordings through an online knowledge processing system, and invite the reader to explore the data with queries based on the concepts discussed in this paper