Image-Based Intermediate Waypoints for Robots in Constrained Navigation
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Solution Overview
Problem
Robotic devices face challenges in navigating constrained environments, often becoming stuck or trapped due to unaccounted obstacles, as they rely on high-level map data that fails to include dynamic objects, leading to inefficient navigation and potential entrapment.
Innovation Solution
A method for generating intermediate waypoints in real-time using image data from sensors, which involves creating a sparse graph based on a body obstacle map, determining valid yaw configurations, and adding intermediate waypoints to the navigation route to avoid obstacles, allowing the robot to navigate around larger dynamic objects effectively.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If the robot relies on high-level map data for navigation, then the navigation system is simple to implement, but the robot becomes stuck or trapped due to unaccounted dynamic obstacles
Solution Approach 1:
The navigation system is segmented into multiple levels: high-level waypoints for overall route guidance and intermediate waypoints for real-time obstacle avoidance. This segmentation allows the system to maintain simplicity at the high level while adding reliability through intermediate real-time adjustments based on sensor data.
Solution Approach 2:
The system performs preliminary action by pre-planning high-level waypoints based on map data, then uses intermediate waypoints generated in real-time to adjust for dynamic obstacles. This preliminary planning combined with real-time adjustment ensures both simplicity and reliability.
2Reliability
If the robot uses real-time sensor data to detect obstacles, then the navigation reliability improves, but the processing time and computational requirements increase
Solution Approach 1:
The system applies local quality by focusing real-time sensor processing only on critical areas around the robot's current position and planned path, rather than processing the entire environment. Intermediate waypoints are generated only where obstacles are detected, reducing overall processing time while maintaining reliability.
Solution Approach 2:
The system uses partial action by generating intermediate waypoints only when necessary (when obstacles are detected) rather than continuously recalculating the entire path. This selective approach maintains reliability while minimizing processing time and computational overhead.
3Reliability
If the robot adds intermediate waypoints to avoid dynamic obstacles, then the navigation reliability improves, but the navigation route complexity increases
Solution Approach 1:
The navigation route is made dynamic by allowing intermediate waypoints to be added or removed in real-time based on obstacle detection. The high-level waypoints remain fixed for overall route stability, while intermediate waypoints provide dynamic obstacle avoidance, balancing reliability and route complexity.
Solution Approach 2:
Intermediate waypoints act as intermediaries between the high-level navigation goals and the robot's immediate obstacle avoidance needs. These intermediary points simplify the control problem by breaking down complex avoidance maneuvers into manageable segments, reducing overall route complexity while maintaining reliability.
Data Source
AI summary
A method for generating intermediate waypoints for a navigation system of a robot includes receiving a navigation route. The navigation route includes a series of high-level waypoints that begin at a starting location and end at a destination location and is based on high-level navigation data. The high-level navigation data is representative of locations of static obstacles in an area the robot is to navigate. The method also includes receiving image data of an environment about the robot from an image sensor 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.