Autonomous Robot Sensor Fusion for Real-Time Responsive Behavior
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Solution Overview
Problem
Existing autonomous robotic systems lack comprehensive integration with their environment and users, struggling with complex human-machine interaction, obstacle avoidance, and task versatility.
Innovation Solution
A modular autonomous robotic system that integrates multiple sensors, cameras, and AI algorithms to acquire sensory and interactive data, enabling real-time decision-making and adaptive behavior for tasks like user tracking, navigation, and cargo management.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If multiple sensors and cameras are integrated for comprehensive environmental perception, then measurement precision and reliability improve, but device complexity increases
Solution Approach 1:
The patent combines multiple sensor types (RGB cameras, depth cameras, LRF, sonars) into an integrated sensing system that operates cooperatively. The sensors are merged into a unified architecture where data from different modalities are processed together to achieve comprehensive environmental perception, resolving the contradiction by organizing complexity into a cohesive system rather than separate independent components.
Solution Approach 2:
The robotic system employs a multi-functional sensing platform that can perform various tasks including obstacle detection, user tracking, navigation, and environmental mapping using the same integrated sensor suite. This universal approach allows the system to improve measurement precision across multiple functions without proportionally increasing complexity for each individual function.
2Adaptability or versatility
If AI algorithms and multiple modules are integrated for autonomous decision-making, then adaptability and task versatility improve, but device complexity increases
Solution Approach 1:
The autonomous system is divided into distinct functional modules (Sensory Module, Locomotion Module, Interaction Module, Power Module, Communication Module, Safety Management Module) each with specific responsibilities. The Central Processing Module coordinates these segmented modules through AI algorithms, allowing the system to achieve high adaptability and task versatility while managing complexity through modular organization and clear interface definitions.
3Productivity
If real-time data processing from multiple sensors is performed, then responsiveness and productivity improve, but use of energy increases
Solution Approach 1:
The system maintains continuous real-time processing of sensor data to enable uninterrupted autonomous operation, user tracking, and obstacle avoidance. The Central Processing Module continuously fuses data from all sensors and coordinates module operations without interruption, ensuring high productivity and responsiveness while managing energy consumption through efficient continuous operation rather than intermittent processing cycles.
Data Source
AI summary
A method and system to improve autonomous robotic system responsive behavior, to control the autonomous responsive behavior of a robotic system based on a set of simultaneously and cooperatively performed real-time action based on a plurality of acquisition sources providing relevant data about the surroundings of the system, wherein the data is processed by a set of modules globally controlled and managed by a Central Processing Module comprising a multitude of control and decision AI algorithms multidirectionally that allow define the autonomous responsive behaviors of the robotic system.