Kai Welke

Toward humanoid manipulation in human-centred environments

In order for humanoid robots to enter human-centred environments, it is indispensable to equip them with manipulative, perceptive and communicative skills necessary for real-time interaction with the environment and humans. The goal of our work is to provide reliable and highly integrated humanoid platforms which on the one hand allow the implementation and tests of various research activities and on the other hand the realization of service tasks in a household scenario. In this paper, we present a new humanoid robot currently being developed for applications in human-centred environments. In addition, we present an integrated grasping and manipulation system consisting of a motion planner for the generation of collision-free paths and a vision system for the recognition and localization of a subset of household objects as well as a grasp analysis component which provides the most feasible grasp configurations for each object.

The Karlsruhe Humanoid Head

The design and construction of truly humanoid robots that can perceive and interact with the environment depends significantly on their perception capabilities. In this paper we present the Karlsruhe Humanoid Head, which has been designed to be used both as part of our humanoid robots ARMAR-IIIa and ARMAR-IIIb and as a stand-alone robot head for studying various visual perception tasks in the context of object recognition and human-robot interaction. The head has seven degrees of freedom (DoF). The eyes have a common tilt and can pan independently. Each eye is equipped with two digital color cameras, one with a wide-angle lens for peripheral vision and one with a narrow-angle lens for foveal vision to allow simple visuo-motor behaviors. Among these are tracking and saccadic motions towards salient regions, as well as more complex visual tasks such as hand-eye coordination. We present the mechatronic design concept, the motor control system, the sensor system and the computational system. To demonstrate the capabilities of the head, we present accuracy test results, and the implementation of both open-loop and closed-loop control on the head.

Towards an Understanding of Channelrhodopsin Function: Simulations Lead to Novel Insights of the Channel Mechanism

Channelrhodopsins (ChRs) are light-gated cation channels that mediate ion transport across membranes in microalgae (vectorial catalysis). ChRs gain increasing attention as useful tools for the analysis of neural networks in tissues and living animals (optogenetics). In fact, various mutagenesis approaches have realized practical applications with high reliability by enhancement of the expression level, channel kinetics control, and color tuning. Furthermore, the recently published x-ray structure has provided valuable information for further atomistic studies and engineering ChRs for a wider application. The present study is a computational attempt to describe the functional mechanism at the atomic level based on the x-ray structure. We present several structural characteristics that are highly involved in ion channel gating and ion transport, including (1) water distribution, (2) cation binding sites, (3) intrahelical hydrogen bond, (4) DC gate, and (5) active site.

Autonomous acquisition of visual multi-view object representations for object recognition on a humanoid robot

The autonomous acquisition of object representations which allow recognition, localization and grasping of objects in the environment is a challenging task, which has shown to be difficult. In this paper, we present a systems for autonomous acquisition of visual object representations, which endows a humanoid robot with the ability to enrich its internal object representation and allows the realization of complex visual tasks. More precisely, we present techniques for segmentation and modeling of objects held in the five-fingered robot hand. Multiple object views are generated by rotating the held objects in the robots field of view. The acquired object representations are evaluated in the context of visual search and object recognition tasks in cluttered environments. Experimental results show successful implementation of the complete cycle from object exploration to object recognition on a humanoid robot.

Structural Model of Channelrhodopsin

Background: The channelrhodopsins are widely used for optogenetic application, whereas a structural model was not available before now. Results: Our modeled structure identifies remarkable structural motifs and elucidates important electrophysiological properties of Channelrhodopsin-2. Conclusion: Channel function relies on the unusual properties of helices 1 and 2. Significance: The atom level structure promotes further understanding of function and may guide the engineering of channelrhodopsins for novel optogenetic applications. Channelrhodopsins (ChRs) are light-gated cation channels that mediate ion transport across membranes in microalgae (vectorial catalysis). ChRs are now widely used for the analysis of neural networks in tissues and living animals with light (optogenetics). For elucidation of functional mechanisms at the atomic level, as well as for further engineering and application, a detailed structure is urgently needed. In the absence of an experimental structure, here we develop a structural ChR model based on several molecular computational approaches, capitalizing on characteristic patterns in amino acid sequences of ChR1, ChR2, Volvox ChRs, Mesostigma ChR, and the recently identified ChR of the halophilic alga Dunaliella salina. In the present model, we identify remarkable structural motifs that may explain fundamental electrophysiological properties of ChR2, ChR1, and their mutants, and in a crucial validation of the model, we successfully reproduce the excitation energy predicted by absorption spectra.

Unconstrained Real-time Markerless Hand Tracking for Humanoid Interaction

Markerless hand tracking of humans can be applied to a broad range of applications, in robotics, animation and natural human-computer interaction. Traditional motion capture and tracking methods involve the usage of devices such as a data glove, or marker points that are fixed and calibrated on the object to perform tracking. Markerless tracking is free from such needs, and therefore allows for more freedom in movement and spontaneous interaction. In this paper, we analyze how a hand tracking system, which reliably tracks arbitrary hand movements can be implemented. We explored a model based approach that uses particle filters for tracking. In this study we also determine the degree to which the inherent parallel properties of particle filter can be exploited to achieve the goal of real-time tracking. We present the effectiveness of the tracking system via the realtime control of a 20 degrees of freedom dexterous robotic hand

Visual servoing for dual arm motions on a humanoid robot

In this work we present a visual servoing approach that enables a humanoid robot to robustly execute dual arm grasping and manipulation tasks. Therefore the target object(s) and both hands are tracked alternately and a combined open-/ closed-loop controller is used for positioning the hands with respect to the target(s). We address the perception system and how the observable workspace can be increased by using an active vision system on a humanoid head. Furthermore a control framework for reactive positioning of both hands using position based visual servoing is presented, where the sensor data streams coming from the vision system, the joint encoders and the force/torque sensors are fused and joint velocity values are generated. This framework can be used for bimanual grasping as well as for two handed manipulations which is demonstrated with the humanoid robot Armar-III that executes grasping and manipulation tasks in a kitchen environment.

Color tuning in binding pocket models of the chlamydomonas-type channelrhodopsins.

We examined the shift of absorption maxima between the chlamydomonas-type channelrhodopsins (ChRs) and bacteriorhodopsin (BR). Starting from the BR X-ray structure, we modeled the color tuning in the binding pockets of the ChRs by mutating up to 28 amino acids in the vicinity of the chromophore. By applying the efficient self-consistent charge density functional tight binding (SCC-DFTB) method in a quantum mechanical/molecular mechanical (QM/MM) framework, including explicit polarization and calculating excitation energies with the semiempirical OM2/MRCI method and the ab initio SORCI method, we have shown that multiple mutations in the binding pocket of BR causes large hypsochromic shifts that are of the same order as the experimentally observed shifts of the absorption maxima between BR and the ChRs. This study further demonstrates that mutations in the proximity of the Schiff base and complex counterion lead to a stronger but more flexible interaction with the retinal, which could serve as a possible explanation for the spectral patterns found in the ChRs.

Active multi-view object search on a humanoid head

Visual search is a common daily human activity and a prerequisite to the interaction with objects encountered in cluttered environments. Humanoid robots that are supposed to take part in human daily life should possess similar capabilities in terms of representing, attending to and recalling objects of interest in order to ensure robust perception in human-centered environments. In this paper, we present necessary processes, memories and representations which allow to identify and store locations of objects, encountered from different angles of view, in a visual search task. In particular, we introduce the so-called Feature Ego-Sphere (FES) as the scene memory for a humanoid robot. Experiments comprising different visual search tasks have been carried out on an active humanoid head equipped with perspective and foveal stereo camera systems. The scene is analyzed actively using both camera systems in order to find instances of searched objects in a consistent and persistent manner.

The robot software framework ArmarX

Abstract With ArmarX we introduce a robot programming environment that has been developed in order to ease the realization of higher level capabilities needed by complex robotic systems such as humanoid robots. ArmarX is built upon the idea that consistent disclosure of the system state strongly facilitates the development process of distributed robot applications. We show the applicability of ArmarX by introducing a robot architecture for a humanoid system and discuss essential aspects based on an exemplary pick and place task. With several tools that are provided by the ArmarX framework, such as graphical user interfaces (GUI) or statechart editors, the programmer is enabled to efficiently build and inspect component based robotics software systems.