Robotic Vehicle Dynamic Path Adjustment for Real-Time Obstacle Avoidance
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Solution Overview
Problem
Existing robotic vehicles struggle with navigating dynamic environments due to reliance on pre-built maps and limited ability to adapt to real-time sensor data, leading to errors in manipulation tasks and obstacle avoidance.
Innovation Solution
Incorporating a dynamic path adjust module that allows robotic vehicles to deviate from predetermined paths based on real-time sensor data, enabling dynamic path adjustments for precise navigation and obstacle avoidance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If robotic vehicles rely on pre-built maps and predetermined paths, then navigation structure is simple and easy to implement, but navigation precision and adaptability deteriorate in dynamic environments
Solution Approach 1:
The patent implements dynamic path adjustment by allowing the robotic vehicle to deviate from predetermined paths based on real-time sensor data. The navigation system transitions from static pre-built maps to dynamic environment modeling, enabling the vehicle to adapt its trajectory continuously according to detected obstacles and environmental changes, thus improving navigation precision in dynamic settings.
Solution Approach 2:
The system incorporates real-time sensor feedback loops where sensor data from the environment is continuously processed to adjust the vehicle's path. This feedback mechanism compares actual environmental conditions with the predetermined path and generates dynamic adjustments, ensuring the vehicle maintains accurate navigation despite environmental variations or obstacles.
2Adaptability or versatility
If robotic vehicles use predetermined paths only, then device complexity is low, but adaptability to real-time environmental changes deteriorates
Solution Approach 1:
The navigation system employs dynamic path generation where the vehicle's trajectory is continuously adjusted based on real-time sensor inputs. This dynamic approach allows the system to adapt to environmental changes such as moving obstacles, changing terrain, or unexpected conditions, significantly improving environmental adaptability while maintaining manageable complexity through modular architecture.
Solution Approach 2:
The robotic vehicle autonomously adjusts its own path without external intervention by processing sensor data and generating dynamic trajectory modifications. This self-service capability enables the vehicle to independently adapt to environmental changes, reducing the need for complex external control systems while improving versatility.
3Manufacturing precision
If robotic vehicles follow predetermined paths strictly, then ease of operation is high, but manipulation precision deteriorates due to target location variations
Solution Approach 1:
The system uses real-time sensor feedback to detect target object locations and dynamically adjusts the vehicle's path to ensure precise positioning for manipulation tasks. This feedback loop compensates for variations in target locations, maintaining high manipulation precision while keeping the operation system relatively simple through automated adjustment algorithms.
Solution Approach 2:
The navigation system dynamically changes path parameters such as position, orientation, and velocity based on real-time sensor data about target locations. This parameter adjustment enables the vehicle to adapt its trajectory for precise manipulation while maintaining ease of operation through automated parameter optimization rather than manual path reprogramming.
Data Source
AI summary
In accordance with one aspect of the inventive concepts, provided is a robotic vehicle comprising at least one processor in communication with at least one computer memory device, a navigation system operatively controlling a drive system to navigate the mobile robot along a predetermined path, at least one sensor configured to acquire real-time sensor data, and a dynamic path adjust system comprising computer program code executable by the at least one processor to cause the navigation system to at least partially and/or temporarily deviate from a current path by generating a dynamically determined path or path segment based on the real-time sensor data and/or an indication in the current path to switch to dynamic path adjust. The robotic vehicle can be configured to switch path to a current and/or original path after executing a dynamically determined path adjustment. A corresponding method is also provided.