Mr. Malte Schilling Profile

Malte Schilling

at Univ Bielefeld

SPIE Involvement:

Author

Publications (2)

This will count as one of your downloads.

You will have access to both the presentation and article (if available).

DOWNLOAD NOW

This content is available for download via your institution's subscription. To access this item, please sign in to your personal account.

Email or Username Forgot your username?

Password Forgot your password?

Show

Keep me signed in

No SPIE account? Create an account

Proceedings Article | 22 May 2007 Paper

Walking capabilities of Gregor controlled through Walknet

Paolo Arena, Luca Patané, Malte Schilling, Josef Schmitz

Proceedings Volume 6592, 65920K (2007) https://doi.org/10.1117/12.724091

KEYWORDS: Robots, Sensors, Device simulation, Field programmable gate arrays, Prototyping, Robotics, Control systems, Biomimetics, Computer architecture, Gait analysis

Read Abstract +

Locomotion control of legged robots is nowadays a field in continuous evolution. In this work a bio-inspired control architecture based on the stick insect is applied to control the hexapod robot Gregor. The control scheme is an extension of Walknet, a decentralized network inspired by the stick insect, that on the basis of local reflexes generates the control signals needed to coordinate locomotion in hexapod robots. Walknet has been adapted to the specific mechanical structure of Gregor that is characterized by specialized legs and a sprawled posture. In particular an innovative hind leg geometry, inspired by the cockroach, has been considered to improve climbing capabilities. The performances of the new control architecture have been evaluated in dynamic simulation environments. The robot has been endowed with distance and contact sensors for obstacle detection. A heading control is used to avoid large obstacles, and an avoidance reflex, as can be found in stick insects, has been introduced to further improve climbing capabilities of the structure. The reported results, obtained in different environmental configurations, stress the adaptive capabilities of the Walknet approach: Even in unpredictable and cluttered environments the walking behaviour of the simulated robot and the robot prototype, controlled through a FPGA based board, remained stable.

Proceedings Article | 22 May 2007 Paper

Mental models for cognitive control

Malte Schilling, Holk Cruse, Josef Schmitz

Proceedings Volume 6592, 659208 (2007) https://doi.org/10.1117/12.721968

KEYWORDS: Sensors, Cognitive modeling, Modulation, Systems modeling, Cognition, Animal model studies, Neural networks, Artificial intelligence, Kinematics, Control systems

Read Abstract +

Even so called "simple" organisms as insects are able to fastly adapt to changing conditions of their environment. Their behaviour is affected by many external influences and only its variability and adaptivity permits their survival. An intensively studied example concerns hexapod walking.^1,2 Complex walking behaviours in stick insects have been analysed and the results were used to construct a reactive model that controls walking in a robot. This model is now extended by higher levels of control: as a bottom-up approach the low-level reactive behaviours are modulated and activated through a medium level. In addition, the system grows up to an upper level for cognitive control of the robot: Cognition - as the ability to plan ahead - and cognitive skills involve internal representations of the subject itself and its environment. These representations are used for mental simulations: In difficult situations, for which neither motor primitives, nor whole sequences of these exist, available behaviours are varied and applied in the internal model while the body itself is decoupled from the controlling modules. The result of the internal simulation is evaluated. Successful actions are learned and applied to the robot. This constitutes a level for planning. Its elements (movements, behaviours) are embodied in the lower levels, whereby their meaning arises directly from these levels. The motor primitives are situation models represented as neural networks. The focus of this work concerns the general architecture of the framework as well as the reactive basic layer of the bottom-up architecture and its connection to higher level functions and its application on an internal model.

My Library

You currently do not have any folders to save your paper to! Create a new folder below.

Folder Name

Folder Description

View contact details

UPDATE YOUR PROFILE

Is this your profile? Update it now.

Sign into your SPIE.org account

Don’t have a profile and want one?

Create an account on SPIE.org

Access to the requested content is limited to institutions that have purchased or subscribe to SPIE eBooks. You are receiving this notice because your organization may not have SPIE eBooks access.*

*Shibboleth/Open Athens users─please sign in to access your institution's subscriptions.

To obtain this item, you may purchase the complete book in print or electronic format on SPIE.org.

ORGANIZATIONAL
Sign in with credentials provided by your organization.

Organizational Username

Organizational Password

Show/Hide Password

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available

Members:

Non-members: ADD TO CART

Keywords/Phrases

Search In:

Publication Years