Local obstacle avoidance for mobile robots based on the method of artificial potentials

Tilove, Robert

doi:10.1109/robot.1990.126041

Cited by 110 publications

(53 citation statements)

References 8 publications

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“…The effect of modifying the entire path at once greatly reduced the problem of becoming trapped in a local minimum of the potential field, however, a collision-free path could still not be guaranteed. Tilove [TIL90].) Second, robots could often favor longer paths to travel around any closely spaced obstacles that they encountered, rather than simply pass untouched between them.…”

Section: Potential Fieldsmentioning

confidence: 99%

Simultaneous Planning and Control for Autonomous Ground Vehicles

Galluzzo¹

2009

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Section: Potential Fieldsmentioning

confidence: 99%

Simultaneous Planning and Control for Autonomous Ground Vehicles

Galluzzo¹

2009

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“…Potential fields present an efficient solution for local obstacle avoidance [13], though with the inherent limitations local minima and the inability to represent hard action constraints. The SPAR algorithm [9] describes a method combining binary constraints with linear objective functions to define a potential over the workspace, but is only used for navigation target selection rather than direct actions.…”

Section: A Multi-robot Role Assignmentmentioning

confidence: 99%

CMDragons: Dynamic passing and strategy on a champion robot soccer team

Bruce

Zickler

Licitra

et al. 2008

2008 IEEE International Conference on Robotics and Automation

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Abstract-After several years of developing multiple RoboCup small-size robot soccer teams, our CMDragons robot team achieved a highly successful level of performance, winning both the 2006 and 2007 competitions without losing a single game. Our small-size team consists of five executing wheeled robots with centralized, off-board perception and decision making. The decision making framework consists of a set of layered components, consisting of perception, evaluation and strategy, robot tactics and skills, and real-time navigation. In this paper, we present the strategy, action selection, and execution aspects of our architecture, with a focus on passing as an example of effective coordinated teamwork. The design enabled our robot team to score using multiple methods, from direct shooting up to 3D passes deflected in midair, resulting in a rich set of actions that were difficult for adversaries to counter. We provide several performance quantified claims supported by testing in our laboratory and in competition settings.

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“…Another key module is the reactive method itself. Some techniques are based on potential methods [10,25,26], but they have limitations [27]. Other techniques compute a set of intermediate motion commands to choose the next one.…”

Section: Related Workmentioning

confidence: 99%

Sensor-based robot motion generation in unknown, dynamic and troublesome scenarios

Mínguez

Montano

2005

Robotics and Autonomous Systems

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A sensor-based motion control system was designed to autonomously drive vehicles free of collisions in unknown, troublesome and dynamic scenarios. The system was developed based on a hybrid architecture with three layers (modeling, planning and reaction). The interaction of the modules was based on a synchronous planner-reactor configuration where the planner computes tactical information to direct the reactivity. Our system differs from previous ones in terms of the choice of the techniques implemented in the modules and in the integration architecture. It can achieve robust and reliable navigation in difficult scenarios that are troublesome for many existing methods. Experiments carried out in these scenarios with a real vehicle confirm the effectiveness of this technique.

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Local obstacle avoidance for mobile robots based on the method of artificial potentials

Cited by 110 publications

References 8 publications

Simultaneous Planning and Control for Autonomous Ground Vehicles

Simultaneous Planning and Control for Autonomous Ground Vehicles

CMDragons: Dynamic passing and strategy on a champion robot soccer team

Sensor-based robot motion generation in unknown, dynamic and troublesome scenarios

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