Adaptive navigation of an omni-drive autonomous mobile robot in unstructured dynamic environments

Abstract

One of the challenges of Autonomous Systems navigating in real world is to deal with the large amounts of uncertainties which are inherent in such environment while maintaining stability. Higher order Fuzzy Logic Systems (FLS), such as Interval Type-2 Fuzzy Logic Systems (IT2FLS), that use type-2 fuzzy sets, can model and handle such uncertainties, and give good performances that outperform their Type-1 counterparts. However, the complexity and computational time of type-reduction process which is strongly related to Membership Functions (MFs) structure and the number of fuzzy rules limit their applications to simple cases in real-time. Artificial Potential Field (APF) approach due to its elegant mathematical analysis, simplicity and its possibility to take into account the dynamic of the system is widely used for autonomous mobile robots navigation. However, the potential field introduced exhibits local minima other than at the goal position of the robot. In this paper, a new real-time navigation approach where we combine the APF and IT2FL approaches is developed and implemented for an omnidrive mobile robot navigating in dynamic unstructured environments. The novelty of the approach is the association of IT2FL to APF and the way in which the two approaches are hybridized (rule base size reduction). The experiments carried out on an omnidrive mobile robot named Robotino show the effectiveness of our approach.

FreeD∗: a mechanism for finding a short and collision free path

“…The collision between the robot and obstacles is avoided by pushing the robot away using the repulsive force. APF is known for its elegant mathematical equations and simplicity in finding the path with very little computation [13].…”

Global navigation approach for assistant robot

“…Around 16 points per path are sent via WiFi. In order to keep the algorithm as simple as possible, Robotino platform was used as a differential robot, in spite of being an omnidirectional (Mao, Wiedmann & Chen, 2011;Mbede, Melingui, Zobo, Merzouki & Bouamama, 2012;Melingui, Chettibi, Merzouki & Mbede, 2013). Then, the robot has to move in straight lines, stop and turn over its axis to perform the movement on the path; the robot repeats this process for each point of the given path.…”

A Cyber Expert System for Auto-Tuning Powered Prosthesis Impedance Control Parameters

“…12,22 This approach was chosen because it permits an adaptive, expandable rule base as more training data become available. 9 Each fuzzy tuner consisted of a fuzzification block, rule-base, inference engine, and defuzzification block.…”