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Section 4.6 Glossary

Reactive Navigation
Navigation that maps current sensor input directly to action without computing a full global map first.
Reactive Behavior
Immediate rule-based response to sensed conditions.
Finite State Machine (FSM)
A way of structuring reactive control as a set of discrete, mutually exclusive states, avoiding disorganized if/else "spaghetti code."
State
One discrete mode of robot behavior within an FSM (for example, DRIVE_FORWARD or TURN_LEFT), active until a transition condition is met.
Transition
A change from one FSM state to another, triggered by a specific sensor reading crossing a defined threshold.
Distance Sensor Array
Multiple distance sensors (for example, Left, Front, and Right) combined to give a robot a wide local perception field, enabling it to decide which direction to turn rather than only when to stop.
Decision Rule
A conditional rule (for example, if-then) that selects actions from sensor measurements.
Obstacle Avoidance
Real-time steering behavior that reduces collision risk around detected obstacles.
Low Latency
Fast response time between sensing and action.
Artificial Potential Fields (APF)
Navigation method that treats the goal as an attractor and obstacles as repellers, using virtual attractive and repulsive forces to guide motion.
Attractive Force (\(F_{\text{att}}\))
Virtual force that pulls the robot toward a goal state.
Repulsive Force (\(F_{\text{rep}}\))
Virtual force that pushes the robot away from obstacles.
Net Force Vector (\(F_{\text{total}}\))
The combined steering influence after summing the attractive and all repulsive force vectors: \(F_{\text{total}} = F_{\text{att}} + F_{\text{rep}}\text{.}\)
Local Minima Trap
APF and other purely reactive failure mode where \(F_{\text{att}} + F_{\text{rep}} = 0\) before the goal is reached, leaving the robot frozen or oscillating with no sensed way out.
Hybrid Architecture
A navigation design that combines a global planner (such as A*) to avoid choosing a path into a trap, with a local reactive controller (FSM or vector avoidance) to handle dynamic obstacles along that path.
Dynamic Environment
An environment where obstacles or conditions can change while the robot is operating.
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