Modular Delivery Robot Fleet for Collaborative Autonomous Navigation
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Solution Overview
Problem
Current autonomous robotic devices are typically designed for specific functions and operate independently, lacking versatility and the ability to collaborate with other robots, which limits their adaptability and efficiency in diverse tasks and environments.
Innovation Solution
A fleet of versatile autonomous mobile robotic chassis equipped with customizable platforms, sensors, processors, and communication systems that enable data capture, mapping, localization, and collaborative task execution, including transportation of items and pods, with mechanisms for loading and unloading, and autonomous navigation and parking.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If autonomous robotic devices are designed for specific functions and operate independently, then device complexity is reduced and ease of manufacture is improved, but adaptability and collaboration capability deteriorate
Solution Approach 1:
The patent implements a universal autonomous robotic platform with standardized interfaces and modular functional units that can perform multiple tasks. The base robot includes universal components such as standardized mounting interfaces, common sensor suites, and adaptable end-effectors that enable the same robot chassis to execute diverse functions including manipulation, transportation, and exploration through configuration changes rather than redesign
Solution Approach 2:
The robotic system is divided into modular functional units (end-effectors, sensors, power supplies, specialized components) that can be independently manufactured and then assembled onto a standardized base platform. This segmentation allows each module to be optimized for its specific function while the overall system maintains versatility through reconfigurable assembly
2Device complexity
If autonomous robotic devices operate independently, then device complexity is reduced, but collaboration capability and task efficiency deteriorate
Solution Approach 1:
Multiple autonomous robotic devices are merged into a coordinated fleet that shares common communication protocols, navigation standards, and task coordination mechanisms. The robots combine their capabilities through collaboration, allowing complex tasks to be distributed across multiple units, thereby increasing overall productivity while maintaining individual device simplicity
Solution Approach 2:
A centralized coordination system or communication network acts as an intermediary between independent robotic devices, enabling them to exchange information, coordinate actions, and collaborate on tasks without requiring complex inter-robot communication protocols in each device. This mediator layer handles task allocation, path coordination, and resource sharing
3Adaptability or versatility
If a versatile autonomous robotic device is customized for different functions, then adaptability is improved, but device complexity and manufacturing difficulty increase
Solution Approach 1:
The robotic system employs dynamically reconfigurable components that can be added, removed, or swapped based on task requirements. The robot's configuration changes from static to dynamic, allowing the same base platform to adapt to different functions through interchangeable modules such as grippers, sensors, and tooling rather than through complex fixed designs
Solution Approach 2:
The system achieves versatility by changing key parameters of the robotic platform such as payload capacity, sensor types, end-effector configurations, and power requirements through modular swaps rather than redesigning the entire system. This parameter-based adaptation allows flexible customization while maintaining a standardized core architecture
4Device complexity
If autonomous robotic devices lack collaboration capability, then device complexity is reduced, but task execution efficiency in diverse environments deteriorates
Solution Approach 1:
Each autonomous robotic device is equipped with self-contained navigation, obstacle detection, and basic decision-making capabilities that allow it to operate independently when needed. This self-service capability reduces the need for complex inter-robot communication while still enabling collaboration when tasks require coordinated effort, as robots can autonomously integrate into fleet operations
Data Source
AI summary
A fleet of delivery robots, each including: a chassis; a storage compartment within which items are stored for transportation; a set of wheels coupled to the chassis; at least one sensor; a processor electronically coupled to the control system and the at least one sensor; and a tangible, non-transitory, machine readable medium storing instructions that when executed by the processor effectuates operations including: capturing, with the at least one sensor, data of an environment and data indicative of movement of the respective delivery robot; generating or updating, with the processor, a first map of the environment based on at least a portion of the captured data; inferring, with the processor, a current location of the respective delivery robot; and actuating, with the processor, the respective delivery robot to execute a delivery task including transportation of at least one item from a first location to a second location.