Shared-Sensor Robot Fleets for Coordinated Warehouse Fulfillment
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Solution Overview
Problem
Current robots operating in warehouses for order fulfillment and inventory management often work independently, lacking the ability to coordinate their actions with other robots, leading to inefficiencies such as redundant tasks and suboptimal resource utilization.
Innovation Solution
Implementing a holistic flow of information between robots and sensors across a warehouse, allowing for real-time shared sensory access, enabling robots to make more informed decisions and operate collectively, thereby optimizing movements, task allocation, and resource usage.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If robots operate independently to complete tasks, then each robot can autonomously perform its assigned tasks, but redundant tasks are performed by different robots at different times and resource utilization is suboptimal
Solution Approach 1:
The patent merges the operations of multiple independent robots into a coordinated fleet that shares sensory information and task assignments. The robot fleet manager consolidates task requests from multiple robots and redistributes them optimally, combining individual robot capabilities into a unified system that eliminates redundant tasks and improves overall productivity.
Solution Approach 2:
The system implements continuous feedback loops where robots share sensory information about their current tasks, battery levels, and environmental observations with the robot fleet manager. This real-time feedback enables dynamic task redistribution and coordination, allowing the system to adapt to changing conditions and optimize resource utilization across the entire fleet.
2Adaptability or versatility
If robots operate independently without coordination, then system complexity is reduced, but resource availability and task optimization are limited
Solution Approach 1:
The robot fleet manager serves as an intermediary between individual robots and the central facility manager. It receives high-level task assignments from the facility manager and translates them into coordinated sub-tasks for individual robots, while also acting as a mediator for sensory information sharing. This intermediary layer enables complex coordination without requiring direct complex interactions between all robots.
Solution Approach 2:
The system segments the control architecture into hierarchical layers: the facility manager handles high-level facility-wide coordination, the robot fleet manager handles robot-specific task allocation and sensory sharing, and individual robots handle execution. This segmentation allows each layer to manage complexity at its appropriate level while maintaining overall system adaptability.
3Productivity
If robots do not share sensory information, then communication overhead is minimized, but collective decision-making and optimization are impaired
Solution Approach 1:
The shared sensory information system serves multiple functions simultaneously: it enables task coordination, provides environmental awareness for safety, supports dynamic task redistribution, and facilitates collective optimization. By making sensory data universally accessible to the robot fleet manager and relevant robots, the system achieves multiple goals without requiring separate communication channels for each function.
Data Source
AI summary
Increased robotic sophistication and more efficient autonomous operation is implemented by providing separate physical autonomous robots shared and remote access to the sensory array and information from the sensory array of one another. Each robot can access a sensor of any other robot, or scans or other information obtained from the sensor of any other robot. The robots leverage the shared sensory access in order to perform batch order fulfillment, dynamic rearrangement of item or tote locations, and opportunistic charging. These coordinated robotic operations based on the shared sensory access increase the efficiency and productivity of the robots without adding resources or hardware to the robots, increasing the speed of the robots, or increasing the number of deployed robots.