Autonomous Locomotion of Humanoid Robots in Presence of Mobile and Immobile Obstacles

Mester, Gyula; Rodić, Aleksandar

doi:10.1007/978-3-642-03737-5_20

Cited by 10 publications

(11 citation statements)

References 4 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In this section fuzzy control is applied to the navigation of the autonomous wheeled mobile robotic platform in unstructured environments with obstacles and slopes [10][11][12][13][14][15].…”

Section: Control Strategy For Wheeled Mobile Robotsmentioning

confidence: 99%

Autonomous Wheeled Mobile Robot Control

Šimon¹

2017

Interdiscip. Descr. Complex Syst.

View full text Add to dashboard Cite

The autonomous wheeled mobile robots are very interesting subject both in scientific research and practical applications. The article deals with the fuzzy control of autonomous wheeled mobile robotic platform motion in an unstructured environment with obstacles. The simulation results show the effectiveness and the validity of the obstacle avoidance behaviour in unstructured environments and the velocity control of a wheeled mobile robotic platform motion of the proposed fuzzy control strategy.

show abstract

Section: Control Strategy For Wheeled Mobile Robotsmentioning

confidence: 99%

Autonomous Wheeled Mobile Robot Control

Šimon¹

2017

Interdiscip. Descr. Complex Syst.

View full text Add to dashboard Cite

show abstract

“…Motors are set up so that two opposites form a pair, which turns clockwise, while the other pair rotates counter-clockwise. This arrangement is chosen so that gyroscopic effects and aerodynamic torques are canceled in trimmed flight [17][18][19][20].…”

Section: Quadrotor Dynamic Modelmentioning

confidence: 99%

“…Often a simple weighted sum is used, but its drawbacks are widely known. Pareto based comparison [19] is the bases of a few popular methods like Non-dominated Sorting GA (NSGA) [22] and Multi-Objective GA (MOGA) [23,25]. A general multi-objective optimization problem consists of n number of scalar minimization objectives where every scalar objective function f i (x) is to be minimized simultaneously, where x is an n-dimensional vector of parameters.…”

Section: Multi-objective Genetic Algorithmsmentioning

confidence: 99%

See 1 more Smart Citation

Fuzzy-Genetic Control of Quadrotors Unmanned Aerial Vehicles

Nemes¹

2016

: Interdiscip. Descr. Complex Syst.

View full text Add to dashboard Cite

This article presents a novel fuzzy identification method for dynamic modelling of quadrotor unmanned aerial vehicles. The method is based on a special parameterization of the antecedent part of fuzzy systems that results in fuzzy-partitions for antecedents. This antecedent parameter representation method of fuzzy rules ensures upholding of predefined linguistic value ordering and ensures that fuzzy-partitions remain intact throughout an unconstrained hybrid evolutionary and gradient descent based optimization process. In the equations of motion the first order derivative component is calculated based on Christoffel symbols, the derivatives of fuzzy systems are used for modelling the Coriolis effects, gyroscopic and centrifugal terms. The non-linear parameters are subjected to an initial global evolutionary optimization scheme and fine tuning with gradient descent based local search. Simulation results of the proposed new quadrotor dynamic model identification method are promising.

show abstract

“…The most important fuzzy logic parameters to be optimized are [5][6][7][8][9][10][11][12][13]:  location and shape of the membership functions,  the truth value of each rules, and  scaling factors.…”

Section: Introductionmentioning

confidence: 99%

Design of the Fuzzy Control Systems Based on Genetic Algorithm for Intelligent Robots

Mester¹

2014

: Interdiscip. Descr. Complex Syst.

Self Cite

View full text Add to dashboard Cite

This paper gives the structure optimization of fuzzy control systems based on genetic algorithm in the MATLAB environment. The genetic algorithm is a powerful tool for structure optimization of the fuzzy controllers, therefore, in this paper, integration and synthesis of fuzzy logic and genetic algorithm has been proposed. The genetic algorithms are applied for fuzzy rules set, scaling factors and membership functions optimization. The fuzzy control structure initial consist of the 3 membership functions and 9 rules and after the optimization it is enough for the 4 DOF SCARA Robot control to compensate for structured and unstructured uncertainty. Fuzzy controller with the generalized bell membership functions can provide better dynamic performance of the robot then with the triangular membership functions. The proposed joint-space controller is computationally simple and had adaptability to a sudden change in the dynamics of the robot. Results of the computer simulation applied to the 4 DOF SCARA Robot show the validity of the proposed method.

show abstract

Autonomous Locomotion of Humanoid Robots in Presence of Mobile and Immobile Obstacles

Cited by 10 publications

References 4 publications

Autonomous Wheeled Mobile Robot Control

Autonomous Wheeled Mobile Robot Control

Fuzzy-Genetic Control of Quadrotors Unmanned Aerial Vehicles

Design of the Fuzzy Control Systems Based on Genetic Algorithm for Intelligent Robots

Contact Info

Product

Resources

About