Autonomous Robot Motion Planning in Dynamic Environments
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Solution Overview
Problem
Conventional autonomous robots are limited to static environments and cannot safely operate alongside humans due to safety concerns, prohibiting their deployment in dynamic environments like fulfillment facilities, where they are needed to move goods and materials efficiently.
Innovation Solution
An autonomous robotic vehicle system with a vehicle management system that includes sensors and computational resources for real-time obstacle detection and trajectory prediction, allowing safe and efficient navigation alongside humans by predicting the motion of dynamic objects and adjusting its path accordingly.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional autonomous robots use safety mechanisms to stop motion upon detecting moving objects, then safety is improved, but productivity deteriorates due to frequent halts in dynamic environments
Solution Approach 1:
The system performs preliminary actions by predicting future positions of dynamic objects using trajectory prediction algorithms before the robot reaches those positions. This allows the robot to plan and adjust its path in advance, maintaining continuous motion while ensuring safety through proactive collision avoidance rather than reactive stopping.
2Device complexity
If conventional autonomous robots are designed for static environments with fixed objects, then device complexity is reduced, but adaptability deteriorates when deployed in dynamic environments with moving objects
Solution Approach 1:
The system transitions from static environmental assumptions to dynamic adaptability by implementing real-time trajectory prediction and motion planning that continuously adjusts to moving objects. The robot adapts its navigation behavior based on predicted human trajectories and environmental changes, enabling versatile operation in dynamic fulfillment center environments.
3Reliability
If autonomous robots halt upon detecting any moving object, then safety is maintained, but loss of time increases due to unnecessary stops in collaborative human-robot environments
Solution Approach 1:
The system implements continuous feedback loops that monitor human object trajectories, robot position, and environmental conditions in real-time. This feedback enables the robot to distinguish between genuine collision risks and safe human movements, adjusting its motion plan dynamically to maintain safety while avoiding unnecessary stops and improving operational efficiency.
Data Source
AI summary
An autonomous robot system to enable automated movement of goods and materials in a dynamic environment including one or more dynamic objects. The autonomous robot system includes an autonomous ground vehicle (AGV) including a vehicle management system. The vehicle management system provides real time resource planning and path optimization to enable the AGV to operate safely and efficiently alongside humans in a dynamic environment. The vehicle management system includes one or more processing devices to execute a moving object trajectory prediction module to predict a trajectory of a dynamic or moving object in a shared environment.