Robot Path Rerouting Around No-Go Zones
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Conventional robots face challenges in navigating environments with obstacles that hinder their movement, leading to potential sticking or failure in completing tasks, as they are often unable to reroute effectively around impassable areas.
Innovation Solution
The implementation of path planning and mapping algorithms that allow a robot to detect rerouting zones and adjust its trajectory to avoid these areas, optimizing the route to ensure minimal length and continuity, using sensor data and user input to determine the best course of action.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a robot follows a predetermined path through an environment, then the robot can maintain simple navigation logic and follow instructions sequentially, but the robot may become stuck or fail when encountering obstacles that greatly hinder its ability to travel
Solution Approach 1:
The patent implements dynamic path rerouting by allowing the robot to transition from a static predetermined path to a dynamic rerouted path when obstacles are detected. The system continuously monitors the environment and adjusts the navigation path in real-time, transforming the rigid follow-path behavior into an adaptive reroute-around-obstacles behavior that maintains reliability while improving adaptability.
Solution Approach 2:
The patent employs feedback mechanisms where sensor data about obstacles is continuously fed back to the navigation system. When obstacles are detected along the predetermined path, this feedback triggers the path rerouting algorithm to calculate and execute an alternative path, enabling the robot to respond to environmental changes and maintain reliable navigation.
2Ease of operation
If a robot makes small deviations from its path to avoid obstacles, then the robot can maintain simple obstacle avoidance, but the robot cannot effectively navigate around large or impassable areas
Solution Approach 1:
The patent segments the navigation problem into two distinct modes: small-scale local avoidance deviations and large-scale global path rerouting. When obstacles are detected, the system determines whether to make minor path adjustments or to execute a complete reroute to an alternative path, enabling effective navigation around both small and large obstacles while maintaining operational simplicity.
Solution Approach 2:
The patent dynamically adjusts the scale of path deviation based on obstacle characteristics. For small obstacles, the robot makes minor local deviations; for large or impassable areas, the system transitions to global rerouting that calculates alternative paths around the entire obstacle region, thereby improving navigation success rate while keeping the control logic relatively simple.
3Reliability
If a robot reroutes around rerouting zones by removing portions of the original route, then the robot can avoid impassable areas, but the remaining route may contain discontinuities or unnavigable segments
Solution Approach 1:
The patent performs preliminary path validation and optimization before executing the rerouted path. After removing portions of the original route that fall within rerouting zones, the system proactively identifies and repairs discontinuities or unnavigable segments in the remaining path, ensuring the rerouted path is complete and navigable before the robot begins traversal.
Solution Approach 2:
The path planning algorithm performs self-correction by automatically detecting and repairing discontinuities in the rerouted path. The system independently identifies gaps or unnavigable segments created by route removal and generates connecting path segments, enabling the robot to autonomously resolve path completeness issues without external intervention.
4Productivity
If a robot optimizes the rerouted path to be of minimal length, then the robot can improve navigation efficiency, but the path planning and optimization processes become more computationally intensive
Solution Approach 1:
The patent applies partial optimization by focusing computational resources on optimizing only the rerouted segments rather than the entire path. The system calculates minimal-length paths for the portions of the route that need rerouting while keeping the unchanged segments of the original path intact, thereby improving navigation efficiency for the affected areas without requiring full-path recomputation.
Data Source
AI summary
Systems and methods for global rerouting of a path of a robot are disclosed herein. According to at least one non-limiting exemplary embodiment, a robot may reroute a path based on one or more rerouting zones, wherein the rerouting zone comprises an area undesirable for the robot to navigate. Accordingly, the present disclosure provides systems and methods for a robot to reroute a path based on the rerouting zones.