A reactive collision avoidance algorithm for nonholonomic vehicles

Wiig, Martin S.; Pettersen, Kristin Y.; Krogstad, Thomas R.

doi:10.1109/ccta.2017.8062714

Cited by 12 publications

(18 citation statements)

References 23 publications

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“…While the algorithm in [17] was based on the kinematics of unicycle-type nonholonomic vehicles, the second-order nonholonomic constraint given by the underactuation makes it necessary to include the sway dynamics. In particular, the total vehicle speed contains a time-varying component from sway, which has to be considered in the analysis in Section V. While the algorithm in [17] provided a desired heading, we will in this paper make the CA algorithm steer the vehicle course instead. We will show that it is thus possible to handle the sway dynamics and guarantee collision avoidance.…”

Section: B Guidance Lawmentioning

confidence: 99%

“…The forward acceleration can be significant during the maneuver, however, which makes the algorithm less suitable for vehicles with forward acceleration constraints. To accommodate such vehicles, the algorithm proposed in [17] extends the approach to vehicles with a constant forward speed. However, only vehicle kinematics are included in the analysis.…”

Section: Introductionmentioning

confidence: 99%

“…The main contribution of this paper is an extension of the CA algorithm presented in [17] to marine vehicles. The marine vehicle has sway dynamics, which can make the vehicle glide sideways into the obstacle.…”

Section: Introductionmentioning

confidence: 99%

“…Moreover, the sway dynamics are underactuated and can therefore only be indirectly controlled through the actuated states. Hence we can no longer use a purely kinematic model, like we could in [17], but have to include the sway dynamics as well.…”

Section: Introductionmentioning

confidence: 99%

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A reactive collision avoidance algorithm for vehicles with underactuated dynamics

Wiig

Pettersen

Krogstad

2017

2017 IEEE 56th Annual Conference on Decision and Control (CDC)

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This paper presents a reactive collision avoidance algorithm, which avoids both static and moving obstacles by keeping a constant avoidance angle between the vehicle velocity vector and the obstacle. In particular, we consider marine vehicles with underactuated sway dynamics, which cannot be directly controlled. This gives an underactuated component in the vehicle velocity, which the proposed algorithm is designed to compensate for. The algorithm furthermore compensates for the obstacle velocity. Conditions are derived under which the sway movement is bounded and collision avoidance is mathematically proved. The theoretical results are supported by simulations. The proposed algorithm makes only limited sensing requirements on the vehicle, is intuitive and suitable for a wide range of vehicles. This includes vehicles with heavy forward acceleration constraints, which is demonstrated by applying the algorithm to a vehicle with constant surge speed.

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Section: B Guidance Lawmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

A reactive collision avoidance algorithm for vehicles with underactuated dynamics

Wiig

Pettersen

Krogstad

2017

2017 IEEE 56th Annual Conference on Decision and Control (CDC)

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“…The vehicle thus both adheres to the heavy forward acceleration cost of many marine vehicles, and becomes more predictable for an external observer. Preliminary results were presented in [27], which only considered vehicle kinematics, and in [28], where the CAA algorithm was further extended to include the underactuated dynamics of the vehicle sway motion.…”

Section: Introductionmentioning

confidence: 99%

Collision Avoidance for Underactuated Marine Vehicles Using the Constant Avoidance Angle Algorithm

Wiig

Pettersen

Krogstad

2020

IEEE Trans. Contr. Syst. Technol.

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Avoiding collisions is a crucial ability for unmanned vehicles. In this paper, we present the constant avoidance angle algorithm, a reactive method for collision avoidance. It can be used to avoid both static and moving obstacles by making the vehicle keep an avoidance angle between itself and the obstacle edge. Unlike many other algorithms, it requires neither knowledge of the complete obstacle shape, nor that the vehicle follows a desired speed trajectory. Rather, safe vehicle headings are provided at the current vehicle speed. Thus, the speed can be used as an input to the algorithm, which provides flexibility and makes the approach suitable for a wide range of vehicles, including vehicles with a limited speed envelope or high acceleration cost. We demonstrate this by applying the algorithm to a marine vehicle described by a full kinematic and dynamic model in three degrees of freedom. We specifically consider vehicles with underactuated sway dynamics, where the vehicle velocity contains a component which cannot be directly controlled. Such dynamics can be highly detrimental to the performance of collision avoidance algorithms, and need to be included in the design and analysis of control systems for such vehicles. In this paper, we compensate for the underactuation by including these dynamics in the underlying analysis and control design. We provide a mathematical analysis of sparse obstacle scenarios, where we derive conditions under which safe avoidance is guaranteed, even for underactuated vehicles. We furthermore show how the modular nature of the algorithm enables it to be combined both with a target reaching and a path following guidance law. Finally, we validate the results both through numerical simulations, and through fullscale experiments aboard the R/V Gunnerus.

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Formation control with collision avoidance for underactuated surface vehicles

Xia

Sun

2021

Asian Journal of Control

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This paper investigates a formation tracking problem of underactuated surface vessels (USVs) with collision avoidance and input saturation. All nonlinearities induced by model uncertainties and disturbances are assumed to be unknown. A design of observer based on neural network is used to recover the velocity data and unknown uncertainties and disturbances. Distributed control laws are designed based on artificial potential functions (APFs), the observer, and a backstepping technique. The APFs combined with a practical category are used to avoid collision. Additional controllers are employed to deal with the input saturation and underactuated problems without affecting the capability of collision avoidance. The stability of formation control system is proved by using the Lyapunov's direct method. Simulation results are performed to illustrate the effectiveness of the proposed strategy.

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A reactive collision avoidance algorithm for nonholonomic vehicles

Cited by 12 publications

References 23 publications

A reactive collision avoidance algorithm for vehicles with underactuated dynamics

A reactive collision avoidance algorithm for vehicles with underactuated dynamics

Collision Avoidance for Underactuated Marine Vehicles Using the Constant Avoidance Angle Algorithm

Formation control with collision avoidance for underactuated surface vehicles

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