Advanced dynamic window based navigation approach using model predictive control

Kiss, Domokos; Tevesz, Gábor

doi:10.1109/mmar.2012.6347927

Cited by 19 publications

(12 citation statements)

References 11 publications

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“…DWA also has the drawback of resulting in local minima problems and nonoptimal motion decision due to constraints of the mobile robot the approach could not manage [75,[102][103][104].…”

Section: Challenges Of Conventional Path Planning Methodsmentioning

confidence: 99%

An Overview of Nature-Inspired, Conventional, and Hybrid Methods of Autonomous Vehicle Path Planning

Ayawli

Chellali

Appiah

et al. 2018

Journal of Advanced Transportation

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Safe and smooth mobile robot navigation through cluttered environment from the initial position to goal with optimal path is required to achieve intelligent autonomous ground vehicles. There are countless research contributions from researchers aiming at finding solution to autonomous mobile robot path planning problems. This paper presents an overview of nature-inspired, conventional, and hybrid path planning strategies employed by researchers over the years for mobile robot path planning problem. The main strengths and challenges of path planning methods employed by researchers were identified and discussed. Future directions for path planning research is given. The results of this paper can significantly enhance how effective path planning methods could be employed and implemented to achieve real-time intelligent autonomous ground vehicles.

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“…DWA also has the drawback of resulting in local minima problems and nonoptimal motion decision due to constraints of the mobile robot the approach could not manage [75,[102][103][104].…”

Section: Challenges Of Conventional Path Planning Methodsmentioning

confidence: 99%

An Overview of Nature-Inspired, Conventional, and Hybrid Methods of Autonomous Vehicle Path Planning

Ayawli

Chellali

Appiah

et al. 2018

Journal of Advanced Transportation

View full text Add to dashboard Cite

show abstract

“…The closed loop dynamics are then derived and used for predicting the AUV trajectories, hence including both sway and controller dynamics in the AUV trajectory prediction. This approach is similar to the one presented in [19], but does not require a linear model and is hence more flexible. In contrast to the approach suggested by [4], the actual equations of motion are used and the kinetics are solved analytically.…”

Section: A New Trajectory Prediction Methodsmentioning

confidence: 99%

A modified dynamic window algorithm for horizontal collision avoidance for AUVs

Eriksen

Breivik

Pettersen

et al. 2016

2016 IEEE Conference on Control Applications (CCA)

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Abstract-Much research has been done on the subject of collision avoidance (COLAV). However, few results are presented that consider vehicles with second-order nonholonomic constraints, such as autonomous underwater vehicles (AUVs). This paper considers the dynamic window (DW) algorithm for reactive horizontal COLAV for AUVs, and uses the HUGIN 1000 AUV in a case study. The DW algorithm is originally developed for vehicles with first-order nonholonomic constraints and is hence not directly applicable for AUVs without resulting in degraded performance. This paper suggests further developments of the DW algorithm to make it better suited for use with AUVs. In particular, a new method for predicting AUV trajectories using a linear approximation which accounts for second-order nonholonomic constraints is developed. The new prediction method, together with a modified search space, reduces the mean square prediction error to about one percent of the original algorithm. The performance and robustness of the modified DW algorithm is evaluated through simulations using a nonlinear model of the HUGIN 1000 AUV.

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“…The DWA is a well-known reactive collision avoidance navigation concept 15 and it has proven performance over a range of extended applications. [16][17][18] The contributions of this article include the following two aspects. First, a novel energy consumption model of the four-wheeled Mecanum robot was built, validated by experiments, and in this article, utilized to extend the DWA local trajectory planner.…”

Section: Introductionmentioning

confidence: 99%

Power-minimization and energy-reduction autonomous navigation of an omnidirectional Mecanum robot via the dynamic window approach local trajectory planning

Xie

Henkel

Stol

et al. 2018

International Journal of Advanced Robotic Systems

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To improve the energy efficiency of the Mecanum wheel, this article extends the dynamic window approach by adding a new energy-related criterion for minimizing the power consumption of autonomous mobile robots. The energy consumption of the Mecanum robot is first modeled by considering major factors. Then, the model is utilized in the extended dynamic window approach-based local trajectory planner to additionally evaluate the omnidirectional velocities of the robot. Based on the new trajectory planning objective that minimizes power consumption, energy-reduction autonomous navigation is proposed via the combinational cost objectives of low power consumption and high speed. Comprehensive experiments are performed in various autonomous navigation task scenarios, to validate the energy consumption model and to show the effectiveness of the proposed technique in minimizing the power consumption and reducing the energy consumption. It is observed that the technique effectively takes advantage of the Mecanum robot's redundant maneuverability, can cope with any type of path and is able to fulfil online obstacle avoidance.

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Advanced dynamic window based navigation approach using model predictive control

Cited by 19 publications

References 11 publications

An Overview of Nature-Inspired, Conventional, and Hybrid Methods of Autonomous Vehicle Path Planning

An Overview of Nature-Inspired, Conventional, and Hybrid Methods of Autonomous Vehicle Path Planning

A modified dynamic window algorithm for horizontal collision avoidance for AUVs

Power-minimization and energy-reduction autonomous navigation of an omnidirectional Mecanum robot via the dynamic window approach local trajectory planning

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