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A snake-based scheme for path planning and control with constraints by distributed visual sensors
Cheng, Yongqiang Jiang, Ping Hu, Yim Fun
Cheng, Yongqiang
Jiang, Ping
Hu, Yim Fun
Publication Date
2014-07
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© Cambridge University Press 2013. The online version of this article is published within an Open Access environment subject to the conditions of the Creative Commons Attribution-NonCommercial-ShareAlike licence . The written permission of Cambridge University Press must be obtained for commercial re-use.
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Accepted for publication
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Abstract
This paper proposes a robot navigation scheme using wireless visual sensors deployed in an environment.
Different from the conventional autonomous robot approaches, the scheme intends to relieve massive on-board
information processing required by a robot to its environment so that a robot or a vehicle with less intelligence can
exhibit sophisticated mobility. A three-state snake mechanism is developed for coordinating a series of sensors to
form a reference path. Wireless visual sensors communicate internal forces with each other along the reference snake
for dynamic adjustment, react to repulsive forces from obstacles, and activate a state change in the snake body from a
flexible state to a rigid or even to a broken state due to kinematic or environmental constraints. A control snake is
further proposed as a tracker of the reference path, taking into account the robot’s non-holonomic constraint and
limited steering power. A predictive control algorithm is developed to have an optimal velocity profile under robot
dynamic constraints for the snake tracking. They together form a unified solution for robot navigation by distributed
sensors to deal with the kinematic and dynamic constraints of a robot and to react to dynamic changes in advance.
Simulations and experiments demonstrate the capability of a wireless sensor network to carry out low-level control
activities for a vehicle.
Version
Accepted Manuscript
Citation
Cheng Y, Jiang P and Hu YF (2014) A snake-based scheme for path planning and control with constraints by distributed visual sensors. Robotica. 32(4): 477-499.
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Article