Distributed Multi-Robot Route Planning for Collision-Free Scaling
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Solution Overview
Problem
Existing multi-robot route planning systems face challenges in scaling up to accommodate large numbers of robots in confined spaces, leading to cumbersome re-planning and interference issues, with existing solutions failing to integrate with existing infrastructure and handle dynamic obstacles effectively.
Innovation Solution
A processor-based method and system for multi-robot route planning that determines route plans based on order values and wait times, optimizing routes by re-computing order values and generating new plans dynamically to avoid collisions and deadlocks, using a decentralized architecture that minimizes communication and eliminates cyclic dependencies.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If centralized route planning is used for multi-robot systems, then route optimization can be achieved, but the system cannot scale and becomes cumbersome when robots are added
Solution Approach 1:
The patent divides the centralized planning problem into distributed local planning modules, where each robot independently plans its route based on local information. This segmentation allows the system to scale by simply adding more independent planning modules without increasing overall system complexity.
Solution Approach 2:
The patent introduces a communication and coordination strategy as an intermediary mechanism that enables distributed robots to share necessary information (such as occupancy grids and route plans) without requiring centralized control. This mediator allows scalable coordination while maintaining distributed architecture.
2Device complexity
If distributed local planning is used where robots plan independently, then scalability is improved, but collision avoidance becomes challenging
Solution Approach 1:
The patent implements feedback mechanisms where robots continuously share their planned routes and occupancy information with others. This feedback loop allows each robot to adjust its local plan based on information from neighboring robots, maintaining collision avoidance while preserving distributed scalability.
Solution Approach 2:
The patent uses preliminary action by having robots perform collision checks and coordinate their routes in advance before executing movements. This proactive coordination prevents collisions while maintaining the benefits of distributed planning.
3Ease of manufacture
If traditional route planning algorithms are used, then simple environments can be handled, but re-planning becomes cumbersome when obstacles or new robots are introduced
Solution Approach 1:
The patent implements dynamic re-planning capabilities where each robot can independently update its route plan in response to changing environmental conditions or new obstacles. The distributed architecture allows this dynamic adaptation to occur locally without requiring system-wide re-planning, maintaining both simplicity and adaptability.
Data Source
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AI summary
The disclosure generally relates to method and system for multi-robot route planning. The method may include determining a route plan of a node based on an order value associated with the node, wherein the order value is distance travelled from the node to one or more nodes in a network, occupying an order slot from a list of orders of the node. The method may further include sending, by a multi-route robot planner, the determined route plan of the node to the one or more nodes in the network and generating a new route plan, in response to sending the determined route plan to one or more nodes, wherein the new route plan is generated based on order value threshold and wait time estimate associated with the node. the method further includes optimizing the generated new route plan of the node to obtain an optimized new route plan, wherein the optimization comprises computing a new order value occupying a new order slot from the list of orders of the node in parallel to change in status of order value of the one or more nodes.