Trajectory Correction Using Repulsive Fields for Dynamic Obstacles
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Solution Overview
Problem
Existing trajectory planning methods fail to effectively navigate mobile devices around both static and dynamic obstacles, preventing smooth destination reach due to the unpredictability of dynamic obstacles.
Innovation Solution
A trajectory correction system and method that determines collision zones between an initial path and a predicted moving path of dynamic objects, forming repulsive objects in the potential field map to generate an obstacle avoidance path using a processor and memory system, incorporating neural networks for real-time path adjustments.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If global planning method is used to obtain all environmental information in advance, then a complete trajectory path can be planned, but it cannot adapt to dynamic obstacles that change during movement
Solution Approach 1:
The system performs preliminary trajectory planning using global environmental information to obtain an initial path. This preliminary action provides a complete trajectory framework that can be subsequently adjusted when dynamic obstacles are detected, combining the benefits of advance planning with real-time adaptability.
Solution Approach 2:
The trajectory planning system transitions from a static global plan to a dynamic adaptive plan by continuously detecting dynamic obstacles and recalculating paths. The potential field map and trajectory are dynamically updated based on real-time obstacle information, allowing the system to adapt to changing environmental conditions while maintaining overall mission objectives.
2Adaptability or versatility
If local planning method is used to obtain environmental information within certain range, then the system can adapt to local changes, but it cannot plan a complete trajectory to avoid dynamic obstacles
Solution Approach 1:
The system merges global planning and local planning methods by combining the complete trajectory framework from global planning with real-time local obstacle detection and avoidance. The global planner provides the overall path to destination while the local planner handles dynamic obstacle avoidance, creating a hybrid approach that achieves both complete trajectory planning and adaptability to local changes.
3Device complexity
If the mobile device follows the initial path without correction, then the path planning is simple, but collision with dynamic obstacles cannot be avoided
Solution Approach 1:
The system implements feedback by continuously monitoring the environment for dynamic obstacles along the initial path. When obstacles are detected, the system provides feedback to the trajectory correction module, which then adjusts the path to avoid collisions. This feedback mechanism maintains relatively simple initial path planning while ensuring reliable collision avoidance through real-time corrections.
4Reliability
If repulsive objects are formed in collision zones, then collision avoidance is improved, but the potential field map complexity increases
Solution Approach 1:
The system applies local quality by forming repulsive objects only in specific collision zones where dynamic obstacles are detected, rather than uniformly across the entire potential field map. This localized approach improves collision avoidance capability in critical areas while minimizing the overall complexity increase of the potential field map structure.
Data Source
AI summary
A trajectory correction method includes: determining whether there is a collision zone according to an initial path and a predicted moving path of a dynamic object; forming a first repulsive object at the corresponding collision zone of an original potential field map in response to determining that there is the collision zone, to obtain a modified potential field map; and obtaining an obstacle avoidance path according to the modified potential field map.