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Reactive navigation assumes only a local knowledge about the environment. For the obstacle avoidance it uses only two motion primitives:
Well-known example of reactive obstacle avoidance is the bug algorithm, which has three variants
Braitenberg vehicles are very simple autonomous agents that use basic sensory-motor connections to produce seemingly cognitive behaviors 1). By adjusting the sensory-motor connections, the robots exhibit different behavior. The vehicle has a differential steering and two sensors at the front of the robot capable of sensing the quantity of a stimuli. Each sensor is directly connected to the actuator using sensory-motor connections based either on inhibition or excitation, which gives four basic behaviors.
A combination of individual vehicle types is referred to as Vehicle 3c that exhibit in a complex environment with several sources of stimulus complex and dynamic behavior that resemble a system of values 2) Adding non-linear activation function to the sensors in Vehicle 4 may produce even more sophisticated behaviors.
The robot senses the distance to the obstacles in front of it. Let the distance to the closest obstacle at the left and right halfplanes of the field of view represent the robot stimuli. Using Braitenberg vehicle model, this sensing can be directly translated into the control command. E.g., using Vehicle 2a the robot will avoid obstacles as it turns away of the stimuli, i.e., it fears the obstacles.