Apparatus and method for planning a robot's driving path

Robot Path Planning Technology Using Attractive and Repulsive Costs for Guidance and Hazard Zones

This technology generates an information grid map by dividing the environment into grids, identifying guidance zones that ensure safety and hazard zones with a high risk of collision. It then calculates attractive and repulsive driving costs for each grid to determine the path with the lowest cost for the robot.

Conventional shortest-path planning methods often suffer from reduced efficiency and safety, as they fail to account for potential collisions with people or complex, unexpected obstacles in real-world environments.

This technology defines guidance and hazard zones on a grid basis using a mapping unit, and a cost calculation unit determines the final driving cost by summing the attractive costs for guidance zones and repulsive costs for hazard zones, while dynamically calibrating constants using real-world driving data. It can be applied to indoor service robots that coexist with humans, enabling movement that is safer and more socially natural than simply taking the shortest path.

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Key Features:

• A mapping unit that divides the surrounding environment into multiple grids to indicate occupied and unoccupied areas
• A configuration that creates an information grid map by setting guidance zones to ensure driving stability and hazard zones with a high risk of collision
• A cost calculation unit that sums the attractive costs for guidance zones and the repulsive costs for hazard zones
• A configuration that derives the path with the lowest driving cost by summing the attractive and repulsive costs

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This invention was developed through sensor-fusion-based environment-adaptive indoor navigation and autonomous intelligent manipulation support for service robots, both provided by the Research Support Division.