A distributed snake algorithm for mobile robots path planning with curvature constraints

Environment Intelligence is becoming ubiquitous. Wireless sensor networks supported environment intelligence is providing an opportunity to service robot navigation to reduce the complexity of conventional centralized and on-board map-building, localization, path-planning and motion control, whilst superior performance can be expected. In terms of robot path planning in a dynamic environment, distributed environment intelligence can take into account both global and local perceptions for path generation and adaptation, which results in better predictability and more prompt reaction. This paper proposes a snake based and distributed path planning algorithm for robot navigation in an intelligent environment with distributed wireless visual sensors. Via communication links between sensors, segments of a path, as an elastic band from start position to goal position, interact each other to react to repulsive forces from obstacles whilst maintain compliance. However, the compliance has to be subject to the robot kinematic constraints and the elastic band may change to rigid or even to a broken state. A state machine is then presented to manage the state switch and control over the network. Simulations and experiments showed that the proposed distributed snake scheme can adapt to dynamic changes in the environment and satisfy the kinematic curvature constraints for the whole path.