Karim Djouani

Intelligent Adaptive Mobile Robot Navigation

This paper deals with the application of a neuro-fuzzy inference system to a mobile robot navigation in an unknown, or partially unknown environment. The final aim of the robot is to reach some pre-defined goal. For this purpose, a sort of a co-operation between three main sub-modules is performed. These sub-modules consist in three elementary robot tasks: following a wall, avoiding an obstacle and running towards the goal. Each module acts as a Sugeno–Takagi fuzzy controller where the inputs are the different sensor information and the output corresponds to the orientation of the robot. The rule-base is generated by the controller after some learning process based on a neural architecture close to that used by Wang and Menger. This leads to adaptive neuro-fuzzy inference systems (ANFIS) (one for each module). The adaptive navigation system (ANFIS), based on integrated reactive-cognitive parts, learns and generates the required knowledge for achieving the desired task. However, the generated rule-base suffers from redundancy and abundance of data, most of which are less useful. This makes the assignment of a linguistic label to the associated variable difficult and sometimes counter-intuitive. Consequently, a simplification phase allowing elimination of redundancy is required. For this purpose, an algorithm based on the class of fuzzy c-means algorithm introduced by Bezdek and we have developed an inclusion structure. Experimental results confirm the meaningfulness of the elaborated methodology when dealing with navigation of a mobile robot in unknown, or partially unknown environment.

New Factorization Techniques and Fast Serial and Parallel Algorithms for Operational Space Control of Robot Manipulators

Abstract In this paper a new factorization technique for computation of inverse of mass matrix, M -1 and the operational space mass matrix, A, as arising in implementation of the operational space control scheme, is presented. This technique results in Schur Complement factorization of both M -1 and A and subsequently new O(N) algorithms for their computation. These O(N) algorithms are highly efficient for parallel computation. To our knowledge, they represent the first algorithms that can be fully parallelized, resulting in both time- and processor-optimal parallel algorithms. Using these algorithms, the OSC scheme can be implemented with an optimal efficiency in both serial and parallel environment. However, in addition to computational efficiency, these algorithms provides a deeper physical insight into the structure of computation which can be exploited for a better design of task space control schemes

Doppler Shift Signature for a MCSs Selection in a VANET

The emergence of Intelligent Transportation Systems has given new hope and an unprecedented number of promising benefits to the transportation industry. However, these benefits are accompanied with inherent challenges due to the higher mobility of the vehicular nodes. One of the major problems faced is the induced Doppler shift in the carrier frequency of the transceiver node. This paper attempts to decrypt the effect of the Doppler shift impact in a Vehicle-to-Vehicle or Vehicle-to-Infrastructure communication system. Mobile nodes that are moving at a relative speed of 25 to 250 km/h are considered. Using a variable Modulation Code Scheme, the degradation effect in term of Bit Error Rate is analyzed under variable signal strength condition. Using the principle of Monte-Carlo, intense simulations are carried with a 95% Confidence Interval. Using the approximation technique, the results obtained from simulations prompted the derivation of a mathematical model. Considering the Bit Error Rate threshold limit defined by the standard, multiple simulation results are optimized to derive the composite result called the Doppler shift signature. A complete mathematical model of the Doppler shift signature accounting for all channel realizations when the Improved Direct Derivation Method is used in a Vehicular Ad-hoc Network is derived and compared against the actual. To assess and explore the effectiveness of the proposed model, several tests are conducted to evaluate the performance of the signature model against other existing rate adaptations, such as Adaptive Modulation Code, Binary phase-shift keying, and Constant. The results from simulation tests demonstrate that the proposed model in conjunction with the Improved Direct Derivation Method offers more than 200% improved throughput compared to its peers Adaptive Modulation Code, Binary phase-shift keying, and Constant.

Kinematic and Inverse Dynamic Analysis of a C5 Joint Parallel Robot

Parallel manipulators have been proposed to overcome accuracy problem in the end effector positioning, exhibited by serial manipulators(Stewart, 1965)(Reboulet, 1988)(Merlet, 2000). These parallel robots are primarly used in the applications for which the considered processes require a high degree of accuracy, high speeds or accelerations. Aircraft simulator (Stewart, 1965), machining tools (Neugebauer et al., 1998)(Poignet et al., 2002), and various other medical applications (Merlet, 2002)(Leroy et al., 2003)(Plitea et al., 2008) constitute some of the many possible applications of parallel robots. The computation of the inverse dynamic model is essential for an effective robot control. In the field of parallel robots, many approaches have been developed for efficient computation of the inverse dynamics. The formalism of d’Alembert has been used to obtain an analytical expression of the dynamics model (Fichter, 1986)(Nakamura & Ghodoussi, 1989). The principle of virtual works has been applied in (Tsai, 2000) for solving the inverse dynamics of the Gough-Stewart platform and in (Zhu et al., 2005) for a Tau parallel robot. Lagrangian formalism is applied in (Leroy et al., 2003) for the dynamics modeling of a parallel robot used as a haptic interface for a surgical simulator. These various approaches do not seem effective for a robot dynamic control under the real time constraint. A better computational efficiency can be achieved by the development of approaches using recursive schemes, in particular, based on the Newton-Euler formulation. Gosselin (Gosselin, 1996) proposed an approach for the computation of the inverse dynamic model of planar and spatial parallel robots, in which all the masses and inertias are taken into account. This proposed method is difficult to generalize for all the parallel architectures. Dasgupda et al (Dasgupta & Choudhury, 1999) applied this method to several parallel manipulators. Khan (Khan, 2005) has developed a recursive algorithm for the inverse dynamics. This method is applied to a 3R planar parallel robot. Bi et al (Bi & Lang, 2006) use the Newton-Euler recursive scheme for the computation of the articular forces of a tripod system. Khalil et al (Khalil & Guegan, 2004) proposed a general method for the inverse and direct dynamic model computation of parallel robots, which is applied to several parallel manipulators (Khalil & Ibrahim, 2007). Despite the large amount of contributions in this field, there is still a need for improving the computational effeciency of the inverse kinematic and dynamic model clculation for real-time control. In this paper, a parallel robot is considered as a multi robot system with 17

Adaptive and conjoint scalar-vector tracking loops for GNSS tracking robustness and positioning integrity

Maintaining robust tracking and positioning integrity in harsh environments is a real challenge for GNSS receivers. This paper considers three possible tracking and navigation solutions to address this challenge. Firstly, a vector tracking loop (VTL) capable of using correlator-based multipath detectors and other signal quality indicators to exclude contaminated satellites from the PVT calculation is proposed. Secondly, an adaptive scalar-vector tracking loop (STL-VTL) that continuously switches between STL and VTL modes based on the state of signal quality indicators is considered. Lastly, a conjoint scalar-vector tracking scheme which maintains STL and VTL modes simultaneously then chooses the measurements to be fed to the navigator based on the state of quality indicators is suggested. To evaluate the performance of the proposed solutions, the trajectory and environment simulator developed by the German Aerospace Center (DLR) is used to simulate GPS signals in harsh suburban and urban conditions. The exclusion of multipath contaminated satellites from PVT calculation improves PVT accuracy and tracking performance. The adaptive and conjoint STL-VTL schemes allow, each in its way, to exploit the advantages of both STL and VTL regarding positioning reliability and tracking robustness.

Fuzzy modeling of MIMO non linear system: complexity reduction

AbstmctThis paper presents the architecture and the design technique underlying (Fuzzy modeling of MIMO non linear System: complexity reduction). In order to generate and optimize multiple input multiple-output MIMO system, a Novel learning based Fuzzy approacb is presented in the case force robot control of 6Dof Parallel Robot. A Standard Fuzzy System (SFS) proposed by Wang and al (lo] is used as architecture for each controller. The resulting rule bases generated by SFS after some learning process suffer from redundancy and overlapping of membership functions. So, a new algoritbm developed in [6] is used for complexity reduction purpose in term of number of membership functions and number of rules. A parallel robot force control is presented to show the effectiveness of the proposed technique. Some experimental results on the free contact non-linear force identification in order to ensure efficient active force control are given.

Transparency improvement of standard fuzzy systems in case of application for control nonlinear system

AbslroclTbis paper propose an effective approach to databased furzy modeling of nonlinear system Using Standard Furzy System proposed by Wangl9l. This approach is proposed for mobile robot reactive conmUers deign, taking into accouot optimnlity of the struetnre and transparency of the resulting f-y system generated. The controllers are designed to emulate mobile robot hsrier behaviors in the form of if-then furzy rules. The resulnng furzy modeling generated by our approach has the foUowiOg distinct futures: 1) Aeqolsition and interpretability of the furzy behaviors in form of If-then rules, 2) Robustness sod uncertainly toler~nre, 3)The analysis of the basic activitie of robot behavior from an erperi view point, 4) Real-time adaptive. Simulatioos results are presented to show the performances and npplicability of the proposed approach.

Practical Adaptive Navigation and Control of a Mobile Robot Using Neuro-Fuzzy Systems

Abstract An Adaptive Navigation System is considered for navigation of an autonomous guided vehicles (such as non-holonomic mobile robot) with kinematics constrains in an unknown environment. The on-line navigation system, based on integrated reactive-cognitive parts, adaptively determines the required actions and/or controllers for the mobile robot. Each controller is adaptive itself, it use an Adaptive Neuro-Fuzzy Inference System (ANFIS). The ANFIS learns and generates the required knowledge for achieving desired goals from the mobile robot behaviour and its environment. Two different phases i.e. the configuration phase and the real time implementation phase are used to train the controllers. Finally, the experimental results confirm that employed methodology works well for mobile robot navigation in an unknown environment.