Real-time obstacle avoidance for manipulators and mobile robots
International Journal of Robotics Research
Behavior-based artificial intelligence
Proceedings of the second international conference on From animals to animats 2 : simulation of adaptive behavior: simulation of adaptive behavior
Action selection for robots in dynamic environments through inter-behaviour bidding
SAB94 Proceedings of the third international conference on Simulation of adaptive behavior : from animals to animats 3: from animals to animats 3
A multivalued logic approach to integrating planning and control
Artificial Intelligence - Special volume on planning and scheduling
Introduction to AI Robotics
Vision and Navigation: The Carnegie Mellon Navlab
Vision and Navigation: The Carnegie Mellon Navlab
Optimal Selection of Uncertain Actions by Maximizing Expected Utility
Autonomous Robots
An architecture to coordinate fuzzy behaviors to control an autonomous robot
Fuzzy Sets and Systems - Special issue: Fuzzy set techniques for intelligent robotic systems
Situated agents can have goals
Robotics and Autonomous Systems
An overview on soft computing in behavior based robotics
IFSA'03 Proceedings of the 10th international fuzzy systems association World Congress conference on Fuzzy sets and systems
Fuzzy behavior-based control of mobile robots
IEEE Transactions on Fuzzy Systems
Fuzzy logic techniques for navigation of several mobile robots
Applied Soft Computing
ICIRA '08 Proceedings of the First International Conference on Intelligent Robotics and Applications: Part I
Development of a new minimum avoidance system for a behavior-based mobile robot
Fuzzy Sets and Systems
Mobile robot behavior coordination using supervisory control of fuzzy discrete event systems
IROS'09 Proceedings of the 2009 IEEE/RSJ international conference on Intelligent robots and systems
An expert fuzzy cognitive map for reactive navigation of mobile robots
Fuzzy Sets and Systems
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This paper presents a novel technique to autonomously select different motor schemas using fuzzy context dependant blending of robot behaviors for navigation. First, a set of motor schemas is formed as behaviors. Both strategic and reactive type schemas have been employed in order to facilitate both the aspects of global and local motion planning. While strategic schemas are formed using the prior knowledge of the environment, the reactive schemas are activated using current sensory data of the robot. For global path planning, a safe path is first created using a Voronoi diagram. For local planning, the Voronoi vertices are treated as immediate subgoals and are used to form schemas leading to achieve optimized traveled distance and goal oriented robot navigation. Two motor schemas are formed as reactive behaviors for obstacle avoidance. The unknown obstacles are modeled using the sensory data. The coordinated behavior is achieved while employing weighed vector summation of the schemas. The adaptation of weights are achieved through a fuzzy inference system where fuzzy rules are used to dynamically generate the weights during navigation. A novel approach is proposed for fuzzy context-dependent blending of schemas. Fuzzy rules are formed using two main criteria into account: the first criterion reasons out the context dependent activity of a schema for achieving goal and the second criterion reasons out cooperative activity of strategic schemas with high priority reactive schemas. Comprehensive results validate that the proposed technique eliminates the existing drawbacks of motor schema approaches available in literature and provides collision free goal oriented robot navigation.