In-Transit Object Shifting With 3D Detection and Adaptive Engagement
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Solution Overview
Problem
Current technologies face challenges in efficiently organizing, routing, and tracking a large number of objects in logistics networks, leading to limitations in handling capacity and precision.
Innovation Solution
The development of an object-shifting system that includes an object-shifting apparatus capable of detecting, locating, identifying, engaging, and shifting objects in automated or semi-automated fashion. This system uses object-detection components to identify objects and object-engaging components to adaptively handle objects of varying sizes and orientations, and is directed by computing devices to optimize object handling.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If automated object detection and shifting systems are implemented, then handling capacity and precision are improved, but device complexity increases
Solution Approach 1:
The system divides object handling into discrete automated steps: detection by sensors, identification by computing devices, engagement by actuators, and shifting by robotic mechanisms. Each function is segmented into independent modular components that can be controlled and optimized separately, resolving the contradiction by making complexity manageable through functional decomposition.
Solution Approach 2:
Manual mechanical object handling is replaced with automated systems using sensors, computing devices, and robotic actuators. This substitution increases handling capacity and precision while the modular architecture of the automated system manages the inherent complexity through standardized interfaces and control protocols.
2Measurement precision
If multiple object-detection components are used to identify objects in three-dimensional space, then measurement precision is improved, but device complexity increases
Solution Approach 1:
Multiple object-detection components (cameras, LIDAR, RFID scanners) are merged into an integrated detection system that operates in three-dimensional space. The computing device combines data from these multiple sources to achieve high measurement precision for object location, identification, and tracking, while the unified control architecture manages the complexity of coordinating multiple sensors.
Solution Approach 2:
The detection system uses multi-functional components that can perform multiple tasks: cameras detect both object presence and visual identification, LIDAR provides both distance measurement and spatial mapping, and RFID readers enable both tracking and identification. This universality reduces the need for separate specialized components, managing complexity while maintaining high precision.
3Adaptability or versatility
If object-engaging components are made adaptable to handle objects of different shapes and sizes, then adaptability is improved, but device complexity increases
Solution Approach 1:
Object-engaging components use dynamic actuators (robotic grippers, adjustable conveyors, movable platforms) that can change their configuration in real-time based on object characteristics detected by the sensing system. This dynamic adaptability allows a single engaging mechanism to handle diverse objects without requiring multiple specialized fixtures, managing complexity through programmable motion control.
Solution Approach 2:
The engaging components modify operational parameters (grip force, position, orientation, speed) based on detected object properties such as size, shape, weight, and fragility. This parameter-based adaptation allows the system to handle varied objects with a unified mechanism, resolving the contradiction by using software-controlled parameter adjustment rather than hardware complexity.
Data Source
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AI summary
Detecting, locating, identifying, engaging, and/or shifting objects in automated or semi-automated fashion as well as methods, systems, apparatuses, and computer-program products therefor. Embodiments used for shifting objects in automated or semi-automated fashion may be implemented in stationary environments, and/or in moving, e.g., in-transit, environments, and may be used to transfer, route, and/or organize objects based on their designated destinations. The embodiments may further be implemented in a logistics network, thereby increasing the efficiency and capacity of the logistics network, among other benefits.