Robot Route Constraints for Safe Navigation in Tight Spaces
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Solution Overview
Problem
Robotic devices face challenges in navigating constrained environments without contacting obstacles or becoming stuck, as conventional navigation systems lack the necessary context to make informed decisions about deviations from the planned route, leading to unsafe and inefficient navigation.
Innovation Solution
A navigation system that utilizes a route specification language providing additional context, including constraints such as yaw and position, to enable the local navigation system to make optimized decisions while maintaining safety and efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional navigation systems are used, then the robot can navigate to the destination, but the robot may contact obstacles or become stuck due to lack of context
Solution Approach 1:
The system performs preliminary actions by generating goal regions and constraint regions before the robot executes navigation. The high-level navigation system creates a route specification with multiple goal regions and constraint regions in advance, providing contextual information that guides the local navigation system to make safe decisions without contacting obstacles.
Solution Approach 2:
The patent introduces an intermediary route specification language that translates high-level navigation goals into detailed local navigation instructions. This intermediary layer includes goal regions, constraint regions, and contextual information that mediates between the high-level destination goal and low-level motion control, preventing obstacle contact while maintaining navigation efficiency.
2Adaptability or versatility
If the robot follows a strict planned route, then the navigation path is clear, but the robot cannot adapt to dynamic obstacles or environmental changes
Solution Approach 1:
The navigation system segments the route into multiple goal regions and constraint regions along the path from start to destination. Each segment can be independently planned and executed, allowing the robot to adapt to local conditions while maintaining overall route coherence. The route specification is divided into discrete navigational primitives that can be selectively applied.
Solution Approach 2:
The system implements dynamics by allowing the local navigation system to deviate from the planned route within constraint regions when dynamic obstacles are detected. The route specification provides a framework that adapts in real-time based on sensor feedback, enabling the robot to navigate around moving obstacles while still achieving the destination goal.
3Reliability
If the robot navigates with larger safety margins, then collision risk is reduced, but the navigation path becomes longer and less efficient
Solution Approach 1:
The patent applies local quality by creating constraint regions with different safety margins at different locations along the navigation path. Instead of applying a uniform safety margin throughout the entire route, the system adjusts the constraint region size and position based on local environmental characteristics, obstacle density, and risk assessment, allowing efficient navigation in safe areas while maintaining larger margins in hazardous zones.
Data Source
AI summary
A method includes receiving sensor data of an environment about a robot and generating a plurality of waypoints and a plurality of edges each connecting a pair of the waypoints. The method includes receiving a target destination for the robot to navigate to and determining a route specification based on waypoints and corresponding edges for the robot to follow for navigating the robot to the target destination selected from waypoints and edges previously generated. For each waypoint, the method includes generating a goal region encompassing the corresponding waypoint and generating at least one constraint region encompassing a goal region. The at least one constraint region establishes boundaries for the robot to remain within while traversing toward the target destination. The method includes navigating the robot to the target destination by traversing the robot through each goal region while maintaining the robot within the at least one constraint region.