This study investigates the nonlinear dynamics of traction for an omniwheel mobile robot platform. A nonlinear slip model is incorporated into the dynamics of the system and the resulting equations of motion are derived using a EulerLagrange formulation. These are additionally transformed into slip-space, where the dynamical equations lend themselves to a convenient analysis of the slip dynamics. The conventional assumptions for ideal rolling are also explored and a reduced expression for the nonlinear dynamics is generated for such situations. Preliminary explorations toward a comprehensive analysis of the dynamics for omniwheel platforms under various control schemes is also initiated.
This paper describes a new cognitive control architecture incorporating episodic memory for the artificial creature Rity, the software robot component of the Ubibot, the ubiquitous robot system. The episodic memory is defined as a scalable structure that stores episodic perceptual snapshots as Rity's experience grows. The system also utilizes a temporally variant spatial map to store spatial information and a higher level procedural memory using Finite State Machines. The system is designed to enable Rity to be cognitive in its approach to task selection through the dual process of experiential and spatial learning. This is brought about through a multi-agent strategy based on six principal modules: perception module, internal state module, behavior selection module, interactive learning module, memory module, and motor module, to control its behavior considering its internal state. Experiments on completion of task and maintenance of ideal internal state are described. The results show that the artificial creature possesses the ability to improve its performance as its experience grows.
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