Mobile Robot Ground Clutter Avoidance Using Footfall History
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Solution Overview
Problem
Existing robot navigation systems fail to effectively avoid smaller obstacles, leading to potential damage to the robot and environment due to stepping on objects like light bulbs or tripping on open buckets, as they do not consider re-routing around such objects during mission execution.
Innovation Solution
A method and system for detecting and classifying 'ground clutter' objects using sensor data and footfall history to navigate around smaller obstacles, improving obstacle avoidance capabilities and reducing damage by modeling the local environment.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the robot uses existing navigation systems to traverse the environment, then the robot can complete missions efficiently, but the robot may step on smaller obstacles causing damage
Solution Approach 1:
The system performs preliminary classification of potential obstacles by analyzing footfall locations from previous mission executions. Before the robot commits to a navigation path, the system identifies locations where the robot previously stepped and determines whether those locations contained obstacles, thereby preparing obstacle avoidance information in advance to prevent damage during actual mission execution
Solution Approach 2:
The system uses feedback from historical mission data, specifically stored footfall location information from previous executions. By comparing current potential obstacle locations with historical footfall data, the system learns from past experiences to identify and avoid obstacles that caused damage in previous missions, continuously improving navigation reliability
2Object-affected harmful factors
If the robot avoids all potential obstacles by re-routing, then the robot prevents damage to itself and the environment, but the navigation complexity and computation increase
Solution Approach 1:
Instead of implementing a universal obstacle avoidance system that treats all potential obstacles equally, the patent applies local quality by classifying obstacles based on their specific characteristics and the robot's historical interaction with them. The system distinguishes between different types of potential obstacles by analyzing footfall locations, applying avoidance only where historically necessary rather than universally, thereby reducing unnecessary navigation complexity
Solution Approach 2:
The system performs preliminary classification of potential obstacles using historical footfall data before actual navigation decisions are made. By pre-processing and categorizing obstacle information from previous missions, the system reduces the computational burden during real-time navigation, as the complex classification work has already been performed in advance
3Measurement precision
If the robot uses sensor data and footfall history to classify ground clutter, then the robot accurately identifies obstacles to avoid, but the data processing time and computational resources increase
Solution Approach 1:
The system performs obstacle classification and analysis during idle periods between missions or during mission planning phases, rather than during critical real-time navigation. By pre-processing sensor data and footfall history to classify ground clutter objects before they are needed for navigation decisions, the system achieves high detection accuracy without sacrificing real-time response during actual mission execution
Solution Approach 2:
The system processes and stores footfall location data from previous missions even when not immediately needed for current navigation. By maintaining a historical record of footfall locations and analyzing this data incrementally over time, the system builds up accurate obstacle classifications without requiring intensive processing during critical navigation moments, effectively distributing the computational load
Data Source
AI summary
Methods and apparatus for navigating a robot along a route through an environment, the route being associated with a mission, are provided. The method comprises identifying, based on sensor data received by one or more sensors of the robot, a set of potential obstacles in the environment, determining, based at least in part on stored data indicating a set of footfall locations of the robot during a previous execution of the mission, that at least one of the potential obstacles in the set is an obstacle, and navigating the robot to avoid stepping on the obstacle.