A hierarchical control and obstacle avoidance system for Unmanned Sea Surface Vehicles

Krishnamurthy, P.; Khorrami, Farshad

doi:10.1109/cdc.2011.6161533

Cited by 9 publications

(4 citation statements)

References 16 publications

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“…In [19], the development of a hierarchical control, path planning, and obstacle avoidance system for autonomous operation of unmanned sea surface vehicles (USSVs) in uncertain cluttered environments was presented. By adopting a modular structure incorporating a robust inner-loop controller and a hierarchical combination of wide-area, intermediate-area, and local-area planning and obstacle avoidance algorithms, the system was designed.…”

Section: The Control Of Unmanned Marine Vehiclesmentioning

confidence: 99%

A survey of motion control for marine vehicles

Han

Wang

2015

2015 34th Chinese Control Conference (CCC)

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The motion control of marine vehicles has attracted much attention from control community. This paper reviews the recent results on the motion control of marine vehicles. The approaches dealing with rudder roll stabilization, heading control, dynamic positioning, unmanned marine vehicles, underactuated marine vehicles, marine thruster control, and controller design for marine vehicles are reviewed.

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Section: The Control Of Unmanned Marine Vehiclesmentioning

confidence: 99%

A survey of motion control for marine vehicles

Han

Wang

2015

2015 34th Chinese Control Conference (CCC)

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“…A side-stepping gait can be easily achieved on the NAO robot simply by prescribing a zero forward speed and a non-zero sideways speed to the built-in walking routine. In [32], a path planning and obstacle avoidance system was developed and experimentally demonstrated on the NAO humanoid robot based on our GODZILA algorithm [28][29][30][31] utilizing a pair of light-weight, inexpensive, and compact ultrasonic sensors that are integrated into the NAO. A sample experimental run is shown in Figure 4.…”

Section: Humanoid Multi-gait Autonomous Navigation In Cluttered Envirmentioning

confidence: 99%

“…In particular, one approach that has been specifically designed to be computationally light-weight so as to address tight memory and processing contraints on small autonomous vehicles is the GODZILA algorithm [28], that enables navigation in completely a priori unknown environments without requiring building of an obstacle map. GODZILA is applicable to various types of unmanned vehicles [29][30][31] as well as humanoid robots [32]. In this paper, the autonomous navigation capabilities in cluttered environments that can be enabled by the human-like gaiting capabilities of biped humanoid robots are addressed.…”

Section: Introductionmentioning

confidence: 99%

A multi-gait approach for humanoid navigation in cluttered environments

Brooks

Krishnamurthy

Khorrami

2014

The 26th Chinese Control and Decision Conference (2014 CCDC)

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A multi-gait approach is proposed in this paper for autonomous humanoid robot navigation and obstacle avoidance in unknown complex cluttered environments. The proposed approach is based on an environment-dependent adaptive switching between multiple gait strategies including, in particular, a new low-profile crawling gait that enables humanoid motion in tight vertically constrained spaces in addition to forward walking and side-stepping gaits. The path planning and obstacle avoidance system is based on the GODZILA algorithm that provides a computationally lightweight approach for navigation in unknown environments without requiring building of an environment map. The new low-profile crawling gait is laterally symmetric and utilizes a cooperative motion of both the hands and feet. The addition of this gait expands the set of environments that can be handled by the humanoid robot. The efficacy of the proposed approach is demonstrated through simulations and experimental studies on a NAO humanoid robot.

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“…In these studies, the uncertainties existing in the vehicle systems are not considered. However, from a practical perspective, the uncertainties such as hydrodynamic effects, wind, and wave disturbances may affect the control accuracy [5,[18][19][20][21][22][23]. Therefore additional schemes should be developed.…”

Section: Introductionmentioning

confidence: 99%

Adaptive dynamic surface control for cooperative path following of underactuated marine surface vehicles via fast learning

Wang

Peng

et al. 2013

IET Control Theory & Applications

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This study presents a solution to the problem of cooperative path following of multiple underactuated marine surface vehicles subject to dynamical uncertainties and ocean disturbances. The dedicated control designs are categorised into two envelopes. One is to steer individual underactuated marine surface vehicle to track a given spatial path; and the other is to synchronise the along-path speeds and path variables under the constraints of an underlying communication network in order to hold a desired formation pattern. Within these two formulations, a robust adaptive path-following controller is first designed for individual vehicle based on neural networks and a dynamic surface control (DSC) technique. Then, the along-path speeds and path variables are synchronised to each vehicle owing to the proposed decentralised synchronisation control law building on graph theory and Lyapunov theory. The key features of the developed controllers are that, first, the DSC technique simplifies the controller design by introducing first-order filters and avoids the calculation of derivatives of virtual control signals. Second, the developed controllers with filtering adaptive laws allow for fast learning without generating high-frequency oscillations in control signals. Rigorous theoretical analysis demonstrates that all signals in the closed-loop system are uniformly ultimately bounded. Simulation results are provided to show the efficacy of the proposed method.

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A hierarchical control and obstacle avoidance system for Unmanned Sea Surface Vehicles

Cited by 9 publications

References 16 publications

A survey of motion control for marine vehicles

A survey of motion control for marine vehicles

A multi-gait approach for humanoid navigation in cluttered environments

Adaptive dynamic surface control for cooperative path following of underactuated marine surface vehicles via fast learning

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