Kai Krieger

Rigid 3D geometry matching for grasping of known objects in cluttered scenes

In this paper, we present an efficient 3D object recognition and pose estimation approach for grasping procedures in cluttered and occluded environments. In contrast to common appearance-based approaches, we rely solely on 3D geometry information. Our method is based on a robust geometric descriptor, a hashing technique and an efficient, localized RANSAC-like sampling strategy. We assume that each object is represented by a model consisting of a set of points with corresponding surface normals. Our method simultaneously recognizes multiple model instances and estimates their pose in the scene. A variety of tests shows that the proposed method performs well on noisy, cluttered and unsegmented range scans in which only small parts of the objects are visible. The main procedure of the algorithm has a linear time complexity resulting in a high recognition speed which allows a direct integration of the method into a continuous manipulation task. The experimental validation with a seven-degree-of-freedom Cartesian impedance controlled robot shows how the method can be used for grasping objects from a complex random stack. This application demonstrates how the integration of computer vision and soft-robotics leads to a robotic system capable of acting in unstructured and occluded environments.

Closed-Loop Behavior of an Autonomous Helicopter Equipped with a Robotic Arm for Aerial Manipulation Tasks

This paper is devoted to the control of aerial robots interacting physically with objects in the environment and with other aerial robots. The paper presents a controller for the particular case of a small-scaled autonomous helicopter equipped with a robotic arm for aerial manipulation. Two types of influences are imposed on the helicopter from a manipulator: coherent and non-coherent influence. In the former case, the forces and torques imposed on the helicopter by the manipulator change with frequencies close to those of the helicopter movement. The paper shows that even small interaction forces imposed on the fuselage periodically in proper phase could yield to low frequency instabilities and oscillations, so-called phase circles.

First analysis and experiments in aerial manipulation using fully actuated redundant robot arm

In this paper we describe a system for aerial manipulation composed of a helicopter platform and a fully actuated seven Degree of Freedom (DoF) redundant industrial robotic arm. We present the first analysis of such kind of systems and show that the dynamic coupling between helicopter and arm can generate diverging oscillations with very slow frequency which we called phase circles. Based on the presented analysis, we propose a control approach for the whole system. The partial decoupling between helicopter and arm - which eliminates the phase circles - is achieved by means of special movement of robotic arm utilizing its redundant DoF. For the underlying arm control a specially designed impedance controller was proposed. In different flight experiments we showcase that the proposed kind of system type might be used in the future for practically relevant tasks. In an integrated experiment we demonstrate a basic manipulation task - impedance based grasping of an object from the environment underlaying a visual object tracking control loop.

On impact decoupling properties of elastic robots and time optimal velocity maximization on joint level

Designing intrinsically elastic robot systems, making systematic use of their properties in terms of impact decoupling, and exploiting temporary energy storage and release during excitative motions is becoming an important topic in nowadays robot design and control. In this paper we treat two distinct questions that are of primary interest in this context. First, we elaborate an accurate estimation of the maximum contact force during simplified human/obstacle-robot collisions and how the relation between reflected joint stiffness, link inertia, human/obstacle stiffness, and human/obstacle inertia affect it. Overall, our analysis provides a safety oriented methodology for designing intrinsically elastic joints and clearly defines how its basic mechanical properties influence the overall collision behavior. This can be used for designing safer and more robust robots. Secondly, we provide a closed form solution of reaching maximum link side velocity in minimum time with an intrinsically elastic joint, while keeping the maximum deflection constraint. This gives an analytical tool for determining suitable stiffness and maximum deflection values in order to be able to execute desired optimal excitation trajectories for explosive motions.

A pilot study in vision-based augmented telemanipulation for remote assembly over high-latency networks

In this paper we present an approach to extending the capabilities of telemanipulation systems by intelligently augmenting a human operators motion commands based on quantitative three-dimensional scene perception at the remote telemanipulation site. This framework is the first prototype of the Augmented Shared-Control for Efficient, Natural Telemanipulation (ASCENT) System. ASCENT aims to enable new robotic applications in environments where task complexity precludes autonomous execution or where low-bandwidth and/or high-latency communication channels exist between the nearest human operator and the application site. These constraints can constrain the domain of telemanipulation to simple or static environments, reduce the effectiveness of telemanipulation, and even preclude remote intervention entirely. ASCENT is a semi-autonomous framework that increases the speed and accuracy of a human operators actions via seamless transitions between one-to-one teleoperation and autonomous interventions. We report the promising results of a pilot study validating ASCENT in a transatlantic telemanipulation experiment between The Johns Hopkins University in Baltimore, MD, USA and the German Aerospace Center (DLR) in Oberpfaffenhofen, Germany. In these experiments, we observed average telemetry delays of 200ms, and average video delays of 2s with peaks of up to 6s for all data. We also observed 75% frame loss for video streams due to bandwidth limits, giving 4fps video.

Exploiting potential energy storage for cyclic manipulation: An analysis for elastic dribbling with an anthropomorphic robot

For achieving dynamic manipulation capabilities that are comparable to human performance in terms of speed, energetic properties, and robustness, intrinsic elasticity is widely proposed as a necessary robot design element. In this paper we show how passive compliance can be exploited for a 6-degree-of-freedom (DoF) cyclic ball dribbling task with a 7-DoF articulated Cartesian impedance controlled DLR Lightweight Robot III. For this, the robot is equipped with an elastic hand, which extends the contact time and therefore, also enlarges both, observability and controllability of the ball. We show via simulation and experiment that it is possible to achieve a stable dynamic cycle based on a 1 DoF analysis from [1] for the main axis together with control strategies for the secondary translations and rotations of the task. The scheme allows also the continuous tracking of a desired dribbling height and horizontal position. As a human is able to dribble blindly, we decided to solve the task by force sensing only, i.e. no vision is used for our approach, however, it could be easily incorporated.

Exploiting elastic energy storage for cyclic manipulation: Modeling, stability, and observations for dribbling

For creating robots that are capable of human like performance in terms of speed, energetic properties, and robustness, intrinsic compliance is a promising design element. In this paper we investigate the effects of elastic energy storage and release for ball dribbling in terms of cycle stability. We base the analysis on error evolution, peak power performance during hand contact, and robustness with respect to varying hand stiffness. As the ball can only be controlled during contact, an intrinsically elastic hand extends the contact time and improves the energetic characteristics of the process. As a human is able to dribble blindly, we decided to focus on the case of contact force sensing only, i.e. no vision is used in our approach.

Intrinsically elastic robots: The key to human like performance

Intrinsically elastic robots, which technically implement some key characteristics of the human muskoskeletal system, have become a major research topic in nowadays robotics. These novel devices open up entirely new control approaches. They base on temporary storage of potential energy and its timed transformation into kinetic energy. In legged locomotion, such considerations have been a common tool for unveiling the respective fundamental physical processes. However, in arm control, elasticities were typically considered parasitic. In this video we outline our efforts in exploiting the inherent capabilities of intrinsically elastic robots in order to bring them closer to human performance. Instead of applying purely kinematic learing-by-demonstration approaches, which are certainly suboptimal, we argue for using model based techniques in order to optimally exploit the system dynamics such that highly dynamic motion and manipulation capabilities can be achieved. In particular, the explicit use of elasticities as temporary energy tanks can be fully exploited, if they are modeled adequately as an integral part of the mechanism. We also believe that such approaches can substantially contribute to the understanding of human motion biomechanics.

Exploiting Elastic Energy Storage for “Blind” Cyclic Manipulation: Modeling, Stability Analysis, Control, and Experiments for Dribbling

For creating robots that are capable of human-like performance in terms of speed, energetic properties, and robustness, intrinsic compliance is a promising design element. In this paper, we investigate the principle effects of elastic energy storage and release for basketball dribbling in terms of open-loop cycle stability. We base the analysis, which is performed for the 1-degree-of-freedom (DoF) case, on error propagation, peak power performance during hand contact, and robustness with respect to varying hand stiffness. As the ball can only be controlled during contact, an intrinsically elastic hand extends the contact time and improves the energetic characteristics of the process. To back up our basic insights, we extend the 1-DoF controller to 6-DoFs and show how passive compliance can be exploited for a 6-DoF cyclic ball dribbling task with a 7-DoF articulated Cartesian impedance controlled robot. As a human is able to dribble blindly, we decided to focus on the case of contact force sensing only, i.e., no visual information is necessary in our approach. We show via simulation and experiment that it is possible to achieve a stable dynamic cycle based on the 1-DoF analysis for the primary vertical axis together with control strategies for the secondary translations and rotations of the task. The scheme allows also the continuous tracking of a desired dribbling height and horizontal position. The approach is also used to hypothesize about human dribbling and is validated with captured data.