Fuzzy-Based Controller for Differential Drive Mobile Robot Obstacle Avoidance

Mitrovic, T Srdjan; Djurović, Željko

doi:10.3182/20100906-3-it-2019.00014

Cited by 11 publications

(7 citation statements)

References 15 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Two experiments on two significantly different robots demonstrated the system's ability to handle unmodelled terrain and robot dynamics and a speed scheduler based on previous experience to address the classic exploration vs. exploitation trade-off, balancing speed and path-tracking errors. Mitrovic et al [13] presented a new methodology for the avoidance of one or more obstacles for the navigation of a differential-drive mobile robot. The approach is based on fuzzy logic with virtual fuzzy magnets and represents a reactive controller for navigation through an unknown environment.…”

Section: Related Workmentioning

confidence: 99%

Model Predictive Control of a Differential-Drive Mobile Robot

Bouzoualegh

Guechi

Kelaiaia

2018

Acta Universitatis Sapientiae Electrical and Mechanical Engineering

View full text Add to dashboard Cite

This paper presents a model predictive control (MPC) for a differential-drive mobile robot (DDMR) based on the dynamic model. The robot’s mathematical model is nonlinear, which is why an input–output linearization technique is used, and, based on the obtained linear model, an MPC was developed. The predictive control law gains were acquired by minimizing a quadratic criterion. In addition, to enable better tuning of the obtained predictive controller gains, torques and settling time graphs were used. To show the efficiency of the proposed approach, some simulation results are provided.

show abstract

Section: Related Workmentioning

confidence: 99%

Model Predictive Control of a Differential-Drive Mobile Robot

Bouzoualegh

Guechi

Kelaiaia

2018

Acta Universitatis Sapientiae Electrical and Mechanical Engineering

View full text Add to dashboard Cite

show abstract

“…while in (Mitrović & Ðurović, 2010b) the output variables of the FRsS are linear and angular velocities of the robot v R and ω R , and in this case (3-4), can be written as:…”

Section: Fictitious Fuzzy Magnets Conceptmentioning

confidence: 99%

Fictitious Fuzzy-Magnet Concept in Solving Mobile–Robot Target Navigation, Obstacle Avoidance and Garaging Problems

Mitrović¹,

Đurović²

2011

Recent Advances in Mobile Robotics

View full text Add to dashboard Cite

“…Li et al [13] considered the cooperative obstacle avoidance algorithm of multi-agent local interaction, so that the agents can bypass the obstacles and aggregate together, then they assembled to the other side of obstacles in a limited time. Mitrovic and Djurovic [14] developed a new way to avoid one or more obstacles by means of the fuzzy logic with virtual fuzzy magnets, which was applied to the navigation of a differential-drive mobile robot. Zhou et al [15] took advantage of Null-Spacebased behavior control, graph theory and finite-time control scheme to design a new expected speed in advance, which could achieve limited-time obstacle avoidance and coordinated tracking.…”

Section: Introductionmentioning

confidence: 99%

Anti-collision and Obstacle Avoidance of Mobile Sensor-plus-actuator Networks over Distributed Parameter Systems with Time-varying Delay

Cui

Zhuang

et al. 2021

Int. J. Control Autom. Syst.

View full text Add to dashboard Cite

This paper addresses the anti-collision problem among mobile sensors-actuators, and settles the obstacle avoidance trouble between dynamic sensors-actuators and erratic obstacles in mobile sensor-actuator networks, which are based on a class of distributed parameter systems with time-varying delay. Initially, the radar obstacle avoidance technology is evolved into an obstacle avoidance function, combined with the anti-collision function. Subsequently, the static output feedback controller of distributed parameter systems is established. Then, by using the abstract development equation theory, operator semigroup approach and Lyapunov stability arguments, the stability analysis of the distributed parameter systems with time-varying delay is carried out. Moreover, an iterative and continuous control force on account of Newton's second law is constructed, which makes anti-collision and obstacle avoidance control of mobile sensors-actuators be realized, and accelerates the state of this delayed system to be stable. Finally, numerical simulation results indicate that the proposed control strategy is effective.

show abstract

Fuzzy-Based Controller for Differential Drive Mobile Robot Obstacle Avoidance

Cited by 11 publications

References 15 publications

Model Predictive Control of a Differential-Drive Mobile Robot

Model Predictive Control of a Differential-Drive Mobile Robot

Fictitious Fuzzy-Magnet Concept in Solving Mobile–Robot Target Navigation, Obstacle Avoidance and Garaging Problems

Anti-collision and Obstacle Avoidance of Mobile Sensor-plus-actuator Networks over Distributed Parameter Systems with Time-varying Delay

Contact Info

Product

Resources

About