Jan Paskarbeit

A hexapod walker using a heterarchical architecture for action selection

Moving in a cluttered environment with a six-legged walking machine that has additional body actuators, therefore controlling 22 DoFs, is not a trivial task. Already simple forward walking on a flat plane requires the system to select between different internal states. The orchestration of these states depends on walking velocity and on external disturbances. Such disturbances occur continuously, for example due to irregular up-and-down movements of the body or slipping of the legs, even on flat surfaces, in particular when negotiating tight curves. The number of possible states is further increased when the system is allowed to walk backward or when front legs are used as grippers and cannot contribute to walking. Further states are necessary for expansion that allow for navigation. Here we demonstrate a solution for the selection and sequencing of different (attractor) states required to control different behaviors as are forward walking at different speeds, backward walking, as well as negotiation of tight curves. This selection is made by a recurrent neural network (RNN) of motivation units, controlling a bank of decentralized memory elements in combination with the feedback through the environment. The underlying heterarchical architecture of the network allows to select various combinations of these elements. This modular approach representing an example of neural reuse of a limited number of procedures allows for adaptation to different internal and external conditions. A way is sketched as to how this approach may be expanded to form a cognitive system being able to plan ahead. This architecture is characterized by different types of modules being arranged in layers and columns, but the complete network can also be considered as a holistic system showing emergent properties which cannot be attributed to a specific module.

Grounding an internal body model of a hexapod walker control of curve walking in a biologically inspired robot

While internal models are a prerequisite for higher-level function, they have to be grounded in lower-level function serving sensorimotor control. In this paper we introduce an internal body model for the control of a hexapod walker. The internal model deals with a highly complex robotic structure of 22 degrees of freedom and coordinates the single joint movements to achieve an overall stable and adaptive walking behavior. It is implemented as a hierarchical recurrent neural network consisting of different levels of abstraction which are tightly intertwined. We demonstrate the feasibility of the concept by applying the model to a simulated robot and show how the different levels of the body model interact and how this allows to scale the model even further. While the internal model is used in this context explicitly for motor control, it is also a predictive model and can be applied for sensor fusion. We discuss how in this way such an internal model offers the flexibility to be utilized in motor control and to be used for planning ahead by a cognitive expansion of the movement controller.

HECTOR, a New Hexapod Robot Platform with Increased Mobility - Control Approach, Design and Communication

At the University of Bielefeld a new bio-inspired, hexapod robot system called HECTOR has been developed and is currently set up. To benefit from bioinspired control approaches it is fundamental to identify the most important body aspects in biological examples and to transfer body features and control approaches as pairs to the technical system. According to this, the main functional characteristics of HECTOR as presented in this paper are the elasticity in the self-contained leg joint-drives with integrated sensory processing capabilities, actuated body joints and in addition a lean bus system for onboard communication.

Distance dependence of near-field fluorescence enhancement and quenching of single quantum dots

Summary In fluorescence microscopy and spectroscopy, energy transfer processes between single fluorophores and fluorophore quencher pairs play an important role in the investigation of molecular distances or orientations. At distances larger than about 3 nm these effects originate predominantly from dipolar coupling. As these experiments are commonly performed in homogenous media, effects at the interface boundaries can be neglected. Nevertheless, the combination of such assays with single-molecule manipulation techniques such as atomic force microscopy (AFM) requires a detailed understanding of the influence of interfaces on dipolar coupling effects. In the presented work we used a combined total internal reflection fluorescence microscopy (TIRFM)–AFM setup to elucidate this issue. We measured the fluorescence emission emanating from single quantum dots as a function of distance from the apex of a gold-coated cantilever tip. As well as fluorescence quenching at close proximity to the tip, we found a nonlinear and nonmonotonic distance dependence of the fluorescence emission. To confirm and interpret our findings we performed calculations on the basis of a simplified multiple multipole (MMP) approach, which successfully supports our experimental data. Moreover, we revealed and quantified the influence of interfering processes such as field enhancement confined at interface boundaries, mirror dipoles and (resonant) dipolar coupling.

Tip-enhanced single molecule fluorescence near-field microscopy in aqueous environment

For nanobiophysical applications, scanning near-field optical microscopy must combine high optical resolution and single fluorescent molecule sensitivity with the ability to operate in aqueous solution. These requirements can be achieved using the electric field enhancement at the tip of illuminated silicon probes for atomic force miscroscopy (AFM), whereby single ATTO-740 dye molecules could be imaged at an optical resolution down to 20 nm under ambient conditions as well as in aqueous solution. Two illumination modes have been tested: (a) bottom illumination in a total internal reflection microscopy setup and (b) direct top illumination, both with dedicated phase-sensitive single photon counting technology in dynamic AFM mode of operation.

Biomechatronics for embodied intelligence of an insectoid robot

In this paper, the design and development of the new hexapod robot HECTOR is described. To benefit from bio-inspired control approaches for walking, it is fundamental to identify the most important morphological and biomechanical aspects and to associate them with biological control approaches whose function principles rely on those special body features. In a second step, these pairs can be transferred to the robot to lay the foundation for embodied intelligence. According to this idea, the main characteristics of HECTOR as presented here are the muscle-like elasticity in the self-contained joint drives with integrated sensor processing capabilities, actuated 2D body segment drives, the layout and orientations of the legs and joint-axes and a lean bus system for onboard communication.

Layout and construction of a hexapod robot with increased mobility

In this paper we concentrate on the design and construction of a novel insectoid walking machine which considers important aspects of arthropods to provide an optimal bodily framework for bioinspired control approaches for walking [4]. In biological systems, control structures and body features have been subject to the same evolutional process. To benefit from bioinspired control approaches it is therefore fundamental to identify the most important body aspects in biological examples and to transfer body features and control approaches as pairs to the technical system. One example for these pairs is the local joint control during the stance phase of walking [9] and elastic features of the joint-driving muscles. A second example is the optimisation of joint-torques and the structural stability of leg segments as a result of the slanted axes in insect legs [6]. Following this train of thought, we introduced novel bioinspired elastic joint drives in the robot. The joint axes orientations, the leg onsets and the overall dimensions of the body and leg segments have been adopted and scaled-up from the biological model. To increase the range of movements, additional 2 DoF joints were introduced in between the individual body segments.

A Bio-Inspired Model for Visual Collision Avoidance on a Hexapod Walking Robot

While navigating their environments it is essential for autonomous mobile robots to actively avoid collisions with obstacles. Flying insects perform this behavioural task with ease relying mainly on information the visual system provides. Here we implement a bio-inspired collision avoidance algorithm based on the extraction of nearness information from visual motion on the hexapod walking robot platform HECTOR. The algorithm allows HECTOR to navigate cluttered environments while actively avoiding obstacles.

Obstacle crossing of a real, compliant robot based on local evasion movements and averaging of stance heights using singular value decomposition

The main advantage of multi-legged robots is the ability to traverse uneven terrain and to overcome obstacles that would impede the movement of a wheeled robot. Compliant joint drives can further improve the performance of legged robot systems by considerably reducing the problems associated with uneven or slippery footholds. Small changes of the foot position in uneven terrain are compensated by the passive joint compliance without the need for fast contact detection and controller responses while the mechanical tension is reduced. On rougher terrain with bigger elevations/depressions of the surface structure, however, a reliable ground contact detection and stance height regulation for each leg is required to distribute the weight of the robot evenly among the legs on ground during stance phase. This work presents a concept that allows the inherently compliant hexapod robot HECTOR to walk on uneven terrain and to overcome moderate obstacles by means of a decentralized walking controller. An important prerequisite is the availability of inherently compliant joint drives with an increased power/weight-ratio.

HECTOR, A Bio-Inspired and Compliant Hexapod Robot

The newly built and currently tested hexapod robot HECTOR is introduced. The robot consists of 18 embedded, custom designed and compliant joint drives based on an integrated elastomer coupling.