Modular Robots for Stable Cooperative Load Transport
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Solution Overview
Problem
Current robotic systems lack the ability to autonomously analyze and adapt to load dynamics, such as dimensions, weight, and stability, and fail to cooperate effectively in transporting varied loads over complex terrain, leading to inefficiencies and potential instability during transport.
Innovation Solution
Fungible robots equipped with sensors like LIDAR, cameras, and strain gauges autonomously estimate load dimensions and stability, determine optimal engagement points, and reconfigure their operation to ensure stable transport by cooperating with other robots to optimize kinematic models and adapt to changing conditions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If robots are designed for specific repeated actions, then they achieve high efficiency and throughput, but they incur high capital costs and have narrow field of application
Solution Approach 1:
The patent applies universality by designing robots with interchangeable end effectors that can perform multiple functions. The robotic system can be reconfigured with different end effectors (grippers, welders, painters, etc.) to handle various tasks across different industries, transforming specialized single-function robots into multi-functional universal robots that maintain high productivity while expanding adaptability
2Adaptability or versatility
If robotic systems are designed to reconfigure shape for terrain, then they improve terrain traversal capability, but they fail to account for load transport complications and autonomous cooperation
Solution Approach 1:
The patent applies dynamics by implementing real-time monitoring and adaptive control of load dynamics. Sensors continuously measure load position, orientation, and stability parameters, and the control system dynamically adjusts robot configurations and coordination strategies to maintain load stability during transport, resolving the contradiction between terrain adaptability and transport reliability
Solution Approach 2:
The patent implements feedback mechanisms where sensors monitor load dynamics and robot performance in real-time, and this information is fed back to the control system which adjusts robot configurations and coordination accordingly. This closed-loop control ensures load stability is maintained while allowing terrain adaptation
3Reliability
If robots autonomously analyze and adapt to load dynamics, then they improve transport stability, but they require complex sensor systems and autonomous decision-making capabilities
Solution Approach 1:
The patent applies self-service by enabling robots to autonomously analyze load dynamics using onboard sensors and independently make decisions about configuration adjustments and coordination strategies. The system serves itself by automatically detecting load characteristics, evaluating stability parameters, and implementing corrective actions without external intervention, achieving transport stability while managing complexity through autonomous operation
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
Enables efficient, stable, and adaptable transport of diverse loads over complex terrain by allowing robots to autonomously assess and adjust their engagement with loads, improving load stability and reducing the risk of damage during transit.
Implementation Method 1
Each of the first and second robots obtains estimates of a width of the load (load width), a length of the load (load length) and a height of the load (load height)
Implementation Method 2
Fungible robots equipped with sensors like LIDAR, cameras, and strain gauges autonomously estimate load dimensions and stability
Implementation Method 3
Fungible robots equipped with sensors like LIDAR, cameras, and strain gauges autonomously estimate load dimensions and stability
Data Source
AI summary
Methods and devices for generally fungible robots that autonomously cooperate to transport a load are provided. A method of transporting a load includes providing first and second robots each having a motive mechanism independently operable from the other. Each robot obtains estimates of a width, length, and height of the load. Each robot can obtain estimates of a weight or stability information of the load. Each robot autonomously determines how to engage the load for transportation based at least partially on the width, length, height, and weight of the load, as well as physical limitations of each robot and the terrain between the load and the delivery point. The robots autonomously cooperate with each other to transport the load. In another aspect, robots autonomously monitor the stability of a load, determine optimum configuration for stable transport of the load, and reconfigure based on stability changes during transport.