Autonomous Navigation Waypoints for Socially Aware Path Planning
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Solution Overview
Problem
Current navigation systems for autonomous vehicles in populated environments are inefficient due to power-draining algorithms, inconsistent interaction with individuals and groups, and inadequate definition of destinations based on social and physical norms.
Innovation Solution
A method for generating navigation paths that considers characteristics of entities in the environment, such as human and non-human entities, using social and physical norms to determine optimal waypoints and sub-paths, minimizing location costs and ensuring safe and harmonious coexistence with humans.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If traditional navigation algorithms are used for autonomous systems in populated environments, then the system can reach its destination, but the power consumption increases and navigation time is excessive
Solution Approach 1:
The navigation path is divided into multiple segmental paths connecting sequential waypoints. Each segmental path represents a portion of the complete navigation route, allowing the system to process and execute navigation in manageable segments rather than computing the entire path at once, thereby reducing computational power consumption while maintaining navigation efficiency
Solution Approach 2:
The system pre-generates a complete global navigation path with multiple waypoints before execution. This preliminary path planning allows the autonomous system to have a predefined route to follow, reducing the need for complex real-time path recalculation and thereby lowering power consumption during actual navigation while improving overall navigation efficiency
2Reliability
If the autonomous system uses fixed interaction protocols with persons, then the system structure is simple, but the interaction consistency with individuals and groups varies
Solution Approach 1:
The navigation system dynamically adjusts its interaction behavior based on real-time detection of entity characteristics. When persons are detected, the system adapts its navigation path and interaction protocol according to the detected formation, number of persons, and orientation. This dynamic adaptation ensures consistent and appropriate interaction with different types of entities while managing system complexity through modular detection and response mechanisms
Solution Approach 2:
The system continuously detects characteristics of entities (persons, objects) in the environment and uses this feedback information to adjust its navigation behavior. The detection module provides real-time information about entity formation, number of persons, and orientation, which feeds back to the path planning module to modify the navigation approach, ensuring consistent interaction protocols are maintained across different scenarios
3Adaptability or versatility
If the destination is defined without considering entity characteristics, then the path planning is simple, but the destination definition does not align with social and physical norms
Solution Approach 1:
The system defines destinations and waypoints with local quality characteristics specific to different entity types. Each waypoint is associated with characteristics such as formation, number of persons, and orientation detected in the local environment. This allows the path planning to adapt to local social and physical norms at each segment of the journey while maintaining an overall structured approach to destination definition
Solution Approach 2:
The system changes navigation parameters based on detected entity characteristics. When entities are detected, the system modifies path planning parameters such as waypoint selection, segmental path generation, and interaction protocols according to the specific characteristics (formation, number of persons, orientation). This parameter adaptation enables the system to align with social and physical norms while managing complexity through controlled parameter modification rather than complete system redesign
Data Source
AI summary
A system and a method for generating a navigation path for an autonomous system. The method comprises receiving data comprising characteristics of entities, the entities defining an environment in which the autonomous system is configured to operate; receiving first instructions causing the autonomous system to identify a destination in the environment; generating a navigation path comprising waypoints to be followed by the autonomous system to reach the destination, the waypoints being generated based on the characteristics of the entities and defining segmental paths; executing second instructions causing the autonomous system to navigate along the navigation path; and upon navigating from a first waypoint to a second waypoint: accessing updates of the characteristics of the entities located in a vicinity of a corresponding segmental path; generating a sub-path between the first waypoint and the second waypoint based on second information; and navigating along the sub-path to reach the second waypoint.