Robot Navigation Switching Between 2D and 3D Path Planning
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Solution Overview
Problem
Existing robot navigation systems face inefficiencies in navigating complex environments due to limitations in both 2D and 3D path planning methods, which can fail to identify collision-free paths, especially when obstacles have varying dimensions and configurations.
Innovation Solution
Implementing a dynamic switching mechanism between 2D and 3D path planning, where 2D planning is used for computational efficiency in open spaces and 3D planning is employed when 2D methods fail to identify a collision-free path, allowing for more accurate evaluation of confined spaces by considering the robot's and obstacles' 3D shapes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If 3D path planning is used for accurate evaluation of confined spaces, then navigation reliability is improved, but computational load increases
Solution Approach 1:
The system dynamically switches between 2D and 3D path planning modes based on real-time environmental assessment. When the robot encounters confined spaces or complex obstacle configurations that 2D planning cannot resolve, it transitions to 3D path planning for accurate evaluation, then returns to 2D mode for routine navigation. This dynamic adaptation resolves the contradiction by applying computationally intensive 3D analysis only when necessary.
Solution Approach 2:
The system changes the dimensionality parameter of path planning from 2D to 3D based on environmental conditions. By adjusting this fundamental parameter, the system can switch between computational efficiency (2D) and navigation reliability (3D), resolving the technical contradiction through parameter transformation rather than maintaining a fixed approach.
2Use of energy by moving object
If 2D path planning is used for computational efficiency, then energy consumption is reduced, but ability to navigate complex environments deteriorates
Solution Approach 1:
The navigation system segments the environment into different complexity zones, applying 2D path planning for simple open spaces and 3D path planning for complex confined areas. This segmentation allows the robot to conserve energy in straightforward regions while maintaining high navigation capability when encountering challenging environments.
Solution Approach 2:
Instead of continuously applying computationally intensive 3D path planning, the system applies it partially—only when 2D planning fails to find a valid path or when environmental sensors detect confined spaces. This partial application of 3D analysis maintains navigation capability while significantly reducing energy consumption compared to continuous 3D planning.
3Measurement precision
If 3D path planning is used continuously, then collision detection accuracy is improved, but processing time increases
Solution Approach 1:
The system performs periodic switching between 2D and 3D path planning based on environmental feedback. Rather than continuous 3D planning, it periodically assesses environmental complexity and transitions to 3D mode only when necessary, thereby maintaining collision detection accuracy while minimizing processing time through rhythmic alternation between planning modes.
Solution Approach 2:
The system performs preliminary 2D path planning to identify potential collision risks before engaging 3D analysis. By pre-screening paths with computationally efficient 2D planning and only applying 3D analysis when 2D planning indicates potential conflicts, the system maintains high collision detection accuracy while avoiding unnecessary processing time.
Data Source
AI summary
Methods, systems, and apparatus, including computer-readable storage devices, for robot navigation using 2D and 3D path planning. In the disclosed method, a robot accesses map data indicating two-dimensional layout of objects in a space and evaluates candidate paths for the robot to traverse. In response to determining that the candidate paths do not include a collision-free path across the space for a two-dimensional profile of the robot, the robot evaluates a three-dimensional shape of the robot with respect to a three-dimensional shape of an object in the space. Based on the evaluation of the three-dimensional shapes, the robot determines a collision-free path to traverse through the space.