Indoor Navigation and Manipulation using a Segway RMP

This project dealt with a Segway RMP, utilizing it in an assistive-technology manner, encompassing navigation and manipulation aspects of robotics. First, background research was conducted to develop a blueprint for the robot. The hardware, software, and configuration of the RMP was updated, and a robotic arm was designed to extend the RMP’s capabilities. The robot was programmed to accomplish autonomous multi-floor navigation through the use of the navigation stack in ROS, image detection, and a GUI. The robot can navigate through the hallways of the building utilizing the elevator. The robotic arm was designed to accomplish tasks such as pressing a button and picking an object up off of a table. The Segway RMP is designed to be utilized and expanded upon as a robotics research platform

Methods for Hand-Eye Coordination of a serial Robot from partial Observations

Precise object manipulation by a robot requires precise knowledge of the position of the robot endeffector relative to the object. By the so-called eye-to-hand coordination, both the position of the object and the position of the robot relative to the camera are determined. In practice, usually the position of the robot base to camera is calibrated in advanced and the position of the robot endeffector relative to the base is calculated by forward kinematics with joint angle confgurations. For the robots working in the human environment, they are constructed with lightweight in order to increase security, which achieves lower stiffness than industrial robots. Thus, the reached position of robot-effector deviates from its commanded position. The work of this thsis is to develop a method based on the image processing to minimize deviations and thus to estimate the real position of the robot endeffector in real time. Thus, the robot end-effector can be guaranteed to precisely grip the target object

Cognitive Reasoning for Compliant Robot Manipulation

Physically compliant contact is a major element for many tasks in everyday environments. A universal service robot that is utilized to collect leaves in a park, polish a workpiece, or clean solar panels requires the cognition and manipulation capabilities to facilitate such compliant interaction. Evolution equipped humans with advanced mental abilities to envision physical contact situations and their resulting outcome, dexterous motor skills to perform the actions accordingly, as well as a sense of quality to rate the outcome of the task. In order to achieve human-like performance, a robot must provide the necessary methods to represent, plan, execute, and interpret compliant manipulation tasks. This dissertation covers those four steps of reasoning in the concept of intelligent physical compliance. The contributions advance the capabilities of service robots by combining artificial intelligence reasoning methods and control strategies for compliant manipulation. A classification of manipulation tasks is conducted to identify the central research questions of the addressed topic. Novel representations are derived to describe the properties of physical interaction. Special attention is given to wiping tasks which are predominant in everyday environments. It is investigated how symbolic task descriptions can be translated into meaningful robot commands. A particle distribution model is used to plan goal-oriented wiping actions and predict the quality according to the anticipated result. The planned tool motions are converted into the joint space of the humanoid robot Rollin' Justin to perform the tasks in the real world. In order to execute the motions in a physically compliant fashion, a hierarchical whole-body impedance controller is integrated into the framework. The controller is automatically parameterized with respect to the requirements of the particular task. Haptic feedback is utilized to infer contact and interpret the performance semantically. Finally, the robot is able to compensate for possible disturbances as it plans additional recovery motions while effectively closing the cognitive control loop. Among others, the developed concept is applied in an actual space robotics mission, in which an astronaut aboard the International Space Station (ISS) commands Rollin' Justin to maintain a Martian solar panel farm in a mock-up environment. This application demonstrates the far-reaching impact of the proposed approach and the associated opportunities that emerge with the availability of cognition-enabled service robots

Reaction Null Space of a multibody system with applications in robotics

This paper provides an overview of implementation examples based on the Reaction Null Space formalism, developed initially to tackle the problem of satellite-base disturbance of a free-floating space robot, when the robot arm is activated. The method has been applied throughout the years to other unfixed-base systems, e.g. flexible-base and macro/mini robot systems, as well as to the balance control problem of humanoid robots. The paper also includes most recent results about complete dynamical decoupling of the end-link of a fixed-base robot, wherein the end-link is regarded as the unfixed-base. This interpretation is shown to be useful with regard to motion/force control scenarios. Respective implementation results are provided

Context-aware Mission Control for Astronaut-Robot Collaboration

Space robot assistants are envisaged as semi-autonomous co-workers deployed to lighten the workload of astronauts in cumbersome and dangerous situations. In view of this, this work considers the prospects on the technology requirements for future space robot operations, by presenting a novel mission control concept for close astronaut-robot collaboration. A decentralized approach is proposed, in which an astronaut is put in charge of commanding the robot, and a mission control center on Earth maintains a list of authorized robot actions by applying symbolic, geometric, and context-specific filters. The concept is applied to actual space robot operations within the METERON SUPVIS Justin experiment. In particular, it is shown how the concept is utilized to guide an astronaut aboard the ISS in its mission to survey and maintain a solar panel farm in a simulated Mars environment

Robotic Deployment of Extraterrestrial Seismic Networks

Manual installation of seismic networks in extraterrestrial environments is risky, expensive and error-prone. A more reliable alternative is the automated deposition with a light-weight robot manipulator. However, inserting a spiked sensor into soil is a challenging task for a robot since the soil parameters are variable and difficult to estimate. Therefore, we investigate an approach to accurate insertion and positioning of geophones using a Cartesian impedance controller with a feed-forward force term. The feed-forward force component of the controller is either estimated using the Fundamental Earth-Moving Equation, the Discrete Element Method or empirically. For the first time, both the geological aspects of the problem as well as the aspects of robotic control are considered. Based on this consideration, the control approach is enhanced by predicting the resistance force of the soil. Experiments with the humanoid robot Rollin’ Justin inserting a geophone into three different soil samples validate the proposed method

Explainability and Knowledge Representation in Robotics: The Green Button Challenge

As robots get closer to human environments, a fundamental task for the community is to design system behaviors that foster trust. In this context, we have posed the "Green Button Challenge": every robot should have a green button that, when pressed, makes the robot explain what it is doing and why, in natural language. In this paper, we motivate why explainability is important in robotics, an why explicit knowledge representations are essential to achieving it. We highlight this with a concrete proof-of-concept implementation on our humanoid space assistant Rollin' Justin, which interprets its PDDL plans to explain what it is doing and why

Entwicklung eines Autonomen Ladevorgangs für das Robotersystem Rollin' Justin

Die vorliegende Arbeit dokumentiert die Entwicklung und die Umsetzung eines autonomen Ladeprozesses fur das Robotersystem Rollin' Justin des Deutschen Zentrums für Luft- und Raumfahrt (DLR) in Oberpfaffenhofen, um dem Robotersystem Langzeitautonomie zu ermöglichen. Sie beinhaltet die einzelnen Entwicklungsschritte von der Fertigstellung der Ladestation uber die Erstellung und die Umsetzung eines Ladekonzepts, sowie die Integration dessen in die autonomen Fähigkeiten des Robotersystems. Dies geschieht anhand der Lokalisation der Ladestation via AprilTags, der Routenplanung mit Hilfe eines hybriden Planungsalgorithmus, der daraufhin folgenden Anfahrt der Ladestation, der genauen Berechnung des Abstands zwischen Roboter und Ladestation und schlussendlich des präzisen Andockens des Roboters an diese. Zum Schluss wird das erstellte Ladekonzept evaluiert und auf mögliche Erweiterungen sowie auf den Nutzen des Systems eingegangen