Model Predictive Control for the navigation of a nonholonomic vehicle with field-of-view constraints

Maniatopoulos, Spyros; Panagou, Dimitra; Kyriakopoulos, Kostas J.

doi:10.1109/acc.2013.6580446

Cited by 31 publications

(17 citation statements)

References 18 publications

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“…for anyz( |t k ) ∈ T (z r ( )) and t ≥ . According to the procedure in Section 3.1, we can build the terminal constraint set to guarantee conditions (25) and (26) as…”

Section: Building Of Terminal Constraint With Choosing Terminal Costmentioning

confidence: 99%

Robust RHC for wheeled vehicles with bounded disturbances

Wang

Feng

et al. 2019

Intl J Robust & Nonlinear

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Summary The robust receding horizon control (RHC) synthesis approach is developed in this paper, for the simultaneous tracking and regulation problem (STRP) of wheeled vehicles with bounded disturbances. Considering the bounded disturbances, we firstly provide a robust positively invariant (RPI) set and associated feedback controller for the perturbed vehicles, which contribute to the foundation of the robust RHC synthesis approach. Then, by extending the tube‐based approach introduced in the article of Mayne et al (robust model predictive control of constrained linear systems with bounded disturbances in Automatica, 2005, vol. 41) to the STRP of wheeled vehicles, we employ the designed RPI set to determine the robust tube and terminal state region, and further construct a nominal optimal control problem. The actual control input is implemented by correcting the solved nominal input with the designed feedback controller. Following the contributed properties of the developed RPI set and extended tube‐based approach, a robust RHC algorithm is finally proposed with the guarantees of recursive feasibility and robust convergence, which can also be adapted for real‐time implementation. Additionally, due to the elaborate control design, the effect of disturbances can be completely nullified to achieve better tracking performance. The effectiveness and advantage of the proposed approach are illustrated by two simulation examples.

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“…for anyz( |t k ) ∈ T (z r ( )) and t ≥ . According to the procedure in Section 3.1, we can build the terminal constraint set to guarantee conditions (25) and (26) as…”

Section: Building Of Terminal Constraint With Choosing Terminal Costmentioning

confidence: 99%

Robust RHC for wheeled vehicles with bounded disturbances

Wang

Feng

et al. 2019

Intl J Robust & Nonlinear

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“…This work is further extended by Salaris et al (2012) for side facing sensors. Maniatopoulos et al (2013) proposes a control law that guides the vehicle towards a desired point by using model predictive control (MPC). In López-Nicolás et al (2010); Salaris et al (2011) different control schemes are proposed to follow the optimal path with an underactuated robot that can turn on the spot.…”

Section: Introductionmentioning

confidence: 99%

Vision Restricted Path Planning and Control for Underactuated Vehicles

Sans-Muntadas¹,

Pettersen²,

Brekke³

2016

IFAC-PapersOnLine

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Autonomous vehicles can obtain navigation information by observing a source with a camera or an acoustic system mounted on the frame of the vehicle. This information properly fused provides navigation information that can overcome the lack of other sources of positioning. However, these systems often have a limited angular field-of-view (FOV). Due to this restriction, motion along some paths will make it impossible to obtain the necessary navigation information as the source is no longer in the vehicle's FOV. This paper proposes both a path planning approach and a guidance control law that allows the vehicle to preserve a certain object or feature inside the FOV while at the same time converging to the proposed path.

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“…Re from (28) and Re from (35) are set to be 0 before 300th second, which means before 300th PER&HAER does not work. After 300th second, the double remapping begins to work.…”

Section: Case 3 (Double Remapping (Perandhaer)mentioning

confidence: 99%

“…Frequent turning, going forward or backward, is required, which is easy to do for unicycle robots, but it is not practical for USVs. In [28], the author presented a novel navigation method for a nonholonomic robot based on Model Predictive Control (MPC). The method can keep sensing with a stationary target although there exist FOV sensing constraints.…”

Section: Introductionmentioning

confidence: 99%

“…(ii) The contributions in [26,28] are developing the formation controllers for USVs under leader-follower structure considering sector-like sensing constraints, and the follower keeps its target in the center of its center, which is hard to form a triangle formation. The contributions in [31] are developing the shortest path control for a robot with FOV constraints to reach a target.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Formation Control of Unmanned Surface Vehicles with Sensing Constraints Using Exponential Remapping Method

Wang

Liu

Hong

2017

Mathematical Problems in Engineering

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This paper presents a formation control strategy for unmanned surface vehicles (USVs) with sensing constraints moving in a leaderfollower formation. Each USV is assumed to be equipped with a vision-based sensor, which is able to get the line-of-sight (LOS) range and bearing information. Most existing literature assumes that the USVs in formation control are with no sensing limitations or with 360-degree sensing fields; however, in our research, the vision-based sensor's capability is restricted due to limited Field of View (FOV) and visual range. We consider that each USV in formation problem is equipped with a sector-like sensing field sensor for the leader-follower formation in two-dimensional space. The formation controller is developed by employing backstepping control technique and exponential remapping. The backstepping controller is designed to stabilize the triangular formation of three USVs, and the proposed exponential remapping method is to deal with the sector-like sensing constraint problem. Comparative analysis with three exponential remapping methods using numerical simulations is given to demonstrate the effectiveness of the proposed method.

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Model Predictive Control for the navigation of a nonholonomic vehicle with field-of-view constraints

Cited by 31 publications

References 18 publications

Robust RHC for wheeled vehicles with bounded disturbances

Robust RHC for wheeled vehicles with bounded disturbances

Vision Restricted Path Planning and Control for Underactuated Vehicles

Formation Control of Unmanned Surface Vehicles with Sensing Constraints Using Exponential Remapping Method

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