Conference Paper

A hexapod walks over irregular terrain using a controller adapted from an insect's nervous system

Electr. Eng. & Comput. Sci. Dept., Case Western Reserve Univ., Cleveland, OH, USA
DOI: 10.1109/IROS.2010.5650200 Conference: Intelligent Robots and Systems (IROS), 2010 IEEE/RSJ International Conference on
Source: IEEE Xplore

ABSTRACT Insects have long been a source of inspiration for the design and implementation of legged robots. Their extraordinary mobility, agility, and adaptability are features sought after when developing competent, useful mobile walkers. Externally witnessed behaviors have been successfully implemented in walking robots for decades with great success. More recent years of biological study have solved some of the mysteries surrounding the actual neurobiological methods for mobilizing these legged wonders. This paper describes the first implementation of these neurobiological mechanisms in a physical hexapod robot that is capable of generating adaptive stepping actions with the same underlying control method as an insect.

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    ABSTRACT: Insect-like walking of six-legged robots on unstructured and rough terrain is considered a challenging task. Furthermore, the properties of the walking ground are considered an important issue and a challenge to insure stable adaptive walking. This paper will shed light on the applied decentralized controller approach for detecting slippery and sandy ground and also presents the proposed strategies to overcome these challenges. The novelty of our approach is the evaluation of the local current consumption and angular position of each leg's joint as somatosensory feedback. Backward walking is proposed as a reflex reaction once a slippery ground is detected and an adaptive walking as soon as the robot detects sandy ground. Our approach is based on an organic computing architecture and was tested on a low-cost version of the OSCAR walking robot.
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    ABSTRACT: Robot builders have often used insects as a source of inspiration when designing their mechanical systems, due to their ability to easily navigate uneven terrain, overcome or avoid obstacles, and adjust gaits based on traveling speed. Robotics has borrowed from nature with varying degrees of abstraction, from physical appearance to observed behaviours. This paper describes the design and construction of a robotic hexapod based on the stick insect, Carausius morosus. Physically, it is an 18.8:1 scale representation of the insect with 3-DoF legs. The to-scale design was chosen to provide similar physical attributes, such as joint and leg locations, sizes, and ranges-of-motion, which will allow more meaningful comparisons between robot performance and actual insect movements (as opposed to arbitrary hexapod designs). A custom-designed leg control board is responsible for deciding leg joint movements based on a model of the neurobiological systems identified in the insect. A distributed network of six boards will be used to control the legs based on internal parameters that can be modulated by descending commands or adaptively altered by ascending sensory signals when interacting with the environment. Our final aim in this work is to add a vision system to create depth maps, which will be used as an input to a learning system, coupled with the mechanical sensory system, such that terrain that triggers reflex actions can be associated with visual cues in order to predictively avoid obstacles and potholes.
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