Vision Restricted Path Planning and Control for Underactuated Vehicles

Sans-Muntadas, Albert; Pettersen, Kristin Y.; Brekke, Edmund

doi:10.1016/j.ifacol.2016.10.343

Cited by 3 publications

(11 citation statements)

References 21 publications

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“…By connecting the initial point p 0 = [r 0 , φ 0 ] and the point p 1 = [d, 0] (Point 1 defined in Section I) with a logarithmic spiral, it allows us to identify the parameter θ. According to [11] the logarithmic spiral connecting the points p 0 and p 1 has the following bearing angle θ:…”

Section: Path Planning With the Docking Spiralmentioning

confidence: 99%

“…In this paper we propose to use the guidance law for logarithmic spirals described in [11] in order for the vehicle to converge to and follow the spiral path. We have chosen this specific guidance law because it is shown in [11] that it preserves the docking station inside the FOV also when steering towards the path. However, we can not apply the guidance from [11] directly to the proposed docking spiral path, because it is only applicable for logarithmic spirals.…”

Section: Guidance Systemmentioning

confidence: 99%

“…We have chosen this specific guidance law because it is shown in [11] that it preserves the docking station inside the FOV also when steering towards the path. However, we can not apply the guidance from [11] directly to the proposed docking spiral path, because it is only applicable for logarithmic spirals. To solve this, we propose an interpolation of the docking spiral path into smaller segments of logarithmic spirals.…”

Section: Guidance Systemmentioning

confidence: 99%

“…Inserting (17) and (19) into (14) we get: Then the general expression of the interpolated path P can be obtained from substituting the waypoints from Equations (19)(20) into the expression of a logarithmic spiral path found in [11,Eq.(2)]:…”

Section: A Interpolation Of the Docking Pathmentioning

confidence: 99%

“…Furthermore, the proposed approach has been experimentally validated by using an articulated AUV (an underwater snake robot) as testbed [10]. To control and guide the robot to the path, the paper introduces a method for interpolating the docking spiral into smaller segments of logarithmic spirals, thereby being able to use the controller described in [11] for path following. This paper is organized in the following way: Section II presents the equations of the docking spirals and analyzes its properties.…”

Section: Introductionmentioning

confidence: 99%

See 4 more Smart Citations

Spiral path planning for docking of underactuated vehicles with limited FOV

Sans-Muntadas¹,

Kelasidi²,

Pettersen³

et al. 2017

2017 IEEE Conference on Control Technology and Applications (CCTA)

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This paper proposes a novel approach for constructing a docking path for underwater vehicles, using a new spiral resulting of combining the Fermat and logarithmic spirals. The proposed spiral path has two properties that will help solve some of the challenges of docking autonomous underactuated vehicles (AUVs). The first property is that the spiral path reaches the entrance of the docking station without curvature, allowing a smooth transition when entering the docking station. The second is that the AUV never exceeds a certain bearing angle with respect to docking station. This last feature allows AUVs equipped with navigation sensors which have a reduced field of view (FOV), such as cameras or acoustic positioning systems, to always preserve the docking station inside the FOV. Furthermore, the paper presents an interpolation of the spiral using waypoints that are connected with segments of logarithmic spirals. This makes it possible to apply existing guidance laws to follow the docking spiral. The proposed spiral docking path has been experimentally tested using an autonomous underwater vehicle.

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Section: Path Planning With the Docking Spiralmentioning

confidence: 99%

Section: Guidance Systemmentioning

confidence: 99%

Section: Guidance Systemmentioning

confidence: 99%

Section: A Interpolation Of the Docking Pathmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Spiral path planning for docking of underactuated vehicles with limited FOV

Sans-Muntadas¹,

Kelasidi²,

Pettersen³

et al. 2017

2017 IEEE Conference on Control Technology and Applications (CCTA)

Self Cite

View full text Add to dashboard Cite

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On the Minimum-Time Control Problem for Differential Drive Robots with Bearing Constraints

Cristofaro

Salaris

Pallottino

et al. 2017

J Optim Theory Appl

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This paper presents a study of analysis of minimum-time trajectories for a differential drive robot equipped with a fixed and limited field-of-view camera, which must keep a given landmark in view during maneuvers. Previous works have considered the same physical problem and provided a complete analysis/synthesis for the problem of determining the shortest paths. The main difference in the two cost functions (length vs. time) lays on the rotation on the spot. Indeed, this maneuver has zero cost in terms of length and hence leads to a 2D shortest path synthesis. On the other hand, in case of minimum time, the synthesis depends also on the orientations of the vehicle. In other words, the not zero cost of the rotation on the spot maneuvers leads to a 3D minimum-time synthesis. Moreover, the shortest paths have been obtained by exploiting the geometric properties of the extremal arcs, i.e., straight lines, rotations on the spot, logarithmic spirals and involute of circles. Conversely, in terms of time, even if the extremal arcs of the minimum-time control problem are exactly the same, the geometric properties of these arcs change, leading to a completely different analysis and characterization of optimal paths. In this paper, after proving the existence of optimal trajectories and showing the extremal arcs of the problem at hand, we provide the control laws that steer the vehicle along these arcs and the time-cost along each of them. Moreover, this being a crucial step toward numerical implementation, optimal trajectories are proved to be characterized by a finite number of switching points between different extremal arcs, i.e., the concatenations of extremal arcs with infinitely many junction times are shown to violate the optimality conditions

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Virtual Landmark-Based Control of Docking Support for Assistive Mobility Devices

Chen

Paez-Granados

Leme

et al. 2021

IEEE/ASME Trans. Mechatron.

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This work proposes an autonomous docking control for nonholonomic constrained mobile robots and applies it to an intelligent mobility device or wheelchair for assisting the user in approaching resting furniture such as a chair or a bed. We defined a virtual landmark inferred from the target docking destination. Then we solve the problem of keeping the targeted volume inside the field of view (FOV) of a tracking camera and docking to the virtual landmark through a novel definition that enables to control for the desired end-pose. We proposed a nonlinear feedback controller to perform the docking with the depth camera's FOV as a constraint. Then a numerical method is proposed to find the feasible space of initial states where convergence could be guaranteed. Finally, the entire system was embedded for real-time operation on a standing wheelchair with the virtual landmark estimation by 3D object tracking with an RGB-D camera and we validated the effectiveness in simulation and experimental evaluations. The results show the guaranteed convergence for the feasible space depending on the virtual landmark location. In the implementation, the robot converges to the virtual landmark while respecting the FOV constraints.Index Terms-Human-assistive robot, mobile robot control, autonomous docking, virtual landmark, FOV constraint I. INTRODUCTION P OWERED wheelchairs operation requires docking as one of the daily activities, many times to very specific poses like driving back to face a chair or laterally to a bed so that, the user can transfer between the wheelchair and other surfaces. Another type of powered wheelchairs -standing mobility devices -has been proposed to enable standing mobility for lower-limb impaired users. i.e., the user locomotes in a standing posture rather than seated. One such example is the Qolo device developed by our group [1], [2]. As with powered wheelchairs, controlling the docking manoeuvre to a conventional chair or a bed is usually difficult for individuals with lower-limb disabilities because twisting their upper body while in the device is rather limited or some users might have limited muscle control. Therefore, we believe it is possible to automate this process for assisting end-users that might find difficulties in this task.

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Vision Restricted Path Planning and Control for Underactuated Vehicles

Cited by 3 publications

References 21 publications

Spiral path planning for docking of underactuated vehicles with limited FOV

Spiral path planning for docking of underactuated vehicles with limited FOV

On the Minimum-Time Control Problem for Differential Drive Robots with Bearing Constraints

Virtual Landmark-Based Control of Docking Support for Assistive Mobility Devices

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