Fault Tolerant and Adaptive Path Planning for Mobile Robots Based on Health Signals

Maas, Raphael; Maehle, Erik

doi:10.1007/bf03345461

Cited by 1 publication

(1 citation statement)

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“…With a distributed and organically inspired gait generation system, OSCAR is able to walk robustly in rough terrain. It can detect anomalies and react accordingly to ensure that it accomplishes its task in the still best possible way, for example by detecting different terrain types and adjusting the gait accordingly [1][2][3] or by amputating legs in case of hardware failures [13] and then choosing a respective path [15]. The distributed network of BCUs and OCUs leads to an emergent walking pattern, similar to those that can be found in real stick insects.…”

Section: Organic Robot Control Architecture (Orca)mentioning

confidence: 87%

Self-reconfigurable control architecture for complex mobile robots

Frost

Stechele

Maehle

2015

It - Information Technology

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Advanced mobile robot systems need to accomplish increasingly complex task sets. However, to solve demanding problems, they are typically optimized to a very restricted set of tasks and environments. This work will therefore propose a self-reconfigurable software and hardware architecture to allow the dynamic optimization of a robot system depending on the current situation, i. e. the current task, the robot inner state, and the environment. The proposed framework is based on organic computing principles and unsupervised machine learning techniques. It further uses dynamically reconfigurable Field Programmable Gate Arrays (FPGA) as hardware accelerators. Preliminary results will be presented, which demonstrate the feasibility of the self-reconfiguration approach.

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