Intermediate Waypoint Generation for Robots in Constrained Navigation
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Robotic devices face challenges in navigating constrained environments by avoiding obstacles not accounted for in high-level maps, often getting stuck or trapped due to dynamic objects not captured by low-level navigation systems.
Innovation Solution
An intermediate waypoint generator system that includes a sparse graph generator, coarse path planner, and waypoint placer to create real-time intermediate waypoints, using body obstacle maps and image data to navigate around dynamic obstacles, ensuring safe maneuvering through yaw restricted zones.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If high-level navigation systems are used for route planning, then overall navigation capability is improved, but the system cannot detect dynamic obstacles not captured in high-level maps
Solution Approach 1:
The navigation system is divided into multiple levels: high-level navigation for overall route planning and low-level navigation for real-time obstacle detection and avoidance. This segmentation allows each level to specialize in specific tasks, with the low-level system compensating for the high-level system's inability to detect dynamic obstacles.
Solution Approach 2:
An intermediate waypoint generation system acts as a mediator between high-level and low-level navigation. It receives the high-level route, generates intermediate waypoints based on real-time sensor data and body obstacle maps, and provides updated navigation guidance that incorporates both high-level planning and low-level obstacle detection.
2Reliability
If low-level navigation systems are used for real-time obstacle avoidance, then dynamic obstacle detection is improved, but the system may get stuck or trapped in constrained environments
Solution Approach 1:
The system pre-generates body obstacle maps and identifies constrained zones before navigation. By anticipating potential trapping situations in advance and planning intermediate waypoints that account for these constraints, the low-level system avoids getting stuck without requiring complex real-time reactions.
Solution Approach 2:
The intermediate waypoint system mediates between aggressive obstacle avoidance and smooth navigation by generating waypoints that guide the robot through constrained environments while maintaining safety margins, preventing the low-level system from making erratic maneuvers that could lead to entrapment.
3Adaptability or versatility
If intermediate waypoints are generated in real-time, then navigation adaptability to dynamic obstacles is improved, but computational complexity increases
Solution Approach 1:
The system generates intermediate waypoints only in specific constrained zones where they are most needed, rather than uniformly across the entire navigation path. This local approach reduces computational complexity by focusing processing resources on critical sections of the route where dynamic obstacles pose the greatest risk.
Solution Approach 2:
The system changes the density and distribution of intermediate waypoints based on environmental parameters such as obstacle density, corridor width, and curvature. In open spaces, fewer waypoints are generated, while in constrained areas, denser waypoint placement occurs, optimizing the balance between adaptability and computational load.
Data Source
Figure 1
Figure 2A~2B
Figure 3
AI summary
A method for generating intermediate waypoints (310) for a navigation system (100) of a robot (10) includes receiving a navigation route (112). The navigation route includes a series of high-level waypoints (210) that begin at a starting location (113) and end at a destination location (114), and is based on high-level navigation data (50) representative of locations of static obstacles in an area the robot is to navigate. The method also includes receiving image data (17) of an environment (8) about the robot from an image sensor (31) and generating at least one intermediate waypoint based on the image data. The method also includes adding the at least one intermediate waypoint to the series of high-level waypoints of the navigation route and navigating the robot from the starting location along the series of high-level waypoints and the at least one intermediate waypoint toward the destination location.