System and method for robotic path planning
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Solution Overview
Problem
Conventional mobile robots face challenges in optimizing both task performance and navigation, particularly in dynamic environments, as they struggle to efficiently plan paths that balance task execution with obstacle avoidance and destination reaching.
Innovation Solution
The method involves a robot determining the cost and benefit of multiple projected paths using a cost map to select an optimal path that allows for efficient task performance while avoiding obstacles and navigating to a destination, incorporating dynamic planning and actuator commands for real-time adjustments.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If conventional mobile robots follow a set path to destination, then navigation efficiency is improved, but ability to perform tasks in dynamic environments deteriorates
Solution Approach 1:
The robot employs dynamic re-planning that continuously adapts the path based on current sensor data and environmental changes. The controller generates new paths in real-time rather than following a pre-set trajectory, allowing the robot to simultaneously maintain navigation efficiency and adapt to dynamic task requirements.
Solution Approach 2:
The path planning is divided into multiple candidate paths that are evaluated separately. The robot segments the navigation task into discrete path options, evaluates each against task requirements and environmental constraints, then selects the optimal path, enabling both efficient navigation and adaptive task performance.
2Reliability
If robot evaluates multiple projected paths, then path selection quality is improved, but computational complexity increases
Solution Approach 1:
The robot evaluates a limited number of candidate paths (e.g., 3-5 options) rather than all possible paths. This partial evaluation approach provides sufficient path selection quality for reliable navigation while keeping computational complexity manageable for real-time operation.
Solution Approach 2:
The robot pre-generates multiple candidate paths before execution and evaluates them in advance. This preliminary path generation and evaluation reduces the computational burden during real-time navigation, maintaining both path selection quality and computational efficiency.
Data Source
Figure 1A
Figure 1B~1C
Figure 2
AI summary
Systems and methods for robotic path planning are disclosed. In some implementations of the present disclosure, a robot can generate a cost map associated with an environment of the robot. The cost map can comprise a plurality of pixels each corresponding to a location in the environment, where each pixel can have an associated cost. The robot can further generate a plurality of masks having projected path portions for the travel of the robot within the environment, where each mask comprises a plurality of mask pixels that correspond to locations in the environment. The robot can then determine a mask cost associated with each mask based at least in part on the cost map and select a mask based at least in part on the mask cost. Based on the projected path portions within the selected mask, the robot can navigate a space.