Robot Actuator Layout for Adaptive Motion With Lower System Complexity
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Solution Overview
Problem
Existing robotic systems face challenges in navigating complex environments due to limitations in sensor-based hardware complexity and inaccuracies in object detection, particularly with dynamic or temporary obstructions, leading to potential collisions and increased power consumption.
Innovation Solution
A vision-based machine learning model that processes image data to create a three-dimensional occupancy network, reducing the need for additional sensors like radar and Lidar, and enhances navigation by projecting objects into a virtual camera space for improved object detection and obstruction identification.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If sensor-based hardware (radar, Lidar) is used to detect dynamic obstructions, then measurement precision is improved, but device complexity increases
Solution Approach 1:
The patent uses a virtual camera to create a digital copy of the physical environment as a three-dimensional occupancy network. This virtual representation replicates obstruction detection capabilities without requiring additional physical sensors like radar or Lidar, thereby maintaining measurement precision while reducing device complexity
Solution Approach 2:
The patent replaces complex mechanical sensor systems (radar, Lidar) with a computational approach using a virtual camera and machine learning model. This substitution eliminates the need for additional hardware components while achieving equivalent or superior obstruction detection through processing existing image data
2Adaptability or versatility
If multiple types of actuators are positioned throughout the robot body, then adaptability is improved, but device complexity increases
Solution Approach 1:
The patent divides the robotic body into multiple segments (torso, shoulders, hips, wrists, elbows, ankles, knees) and positions specific types of actuators at each segment. This segmentation allows each actuator to perform specialized functions for its local joint while the coordinated action of all segments achieves complex overall movement, thereby improving adaptability without proportionally increasing system complexity
Solution Approach 2:
The patent employs six different types of actuators (rotary and linear) that can be positioned at various locations throughout the robot body. Each actuator type is designed to handle specific movement requirements, but the system as a whole achieves universal movement capability across multiple degrees of freedom, allowing the robot to perform diverse tasks with a modular actuator architecture
Data Source
AI summary
A system or methodology of controlling movement of a robot (600) using actuators, the system can include one or more first type of actuators (1002) positioned at torso, shoulder, and hip locations of the robot; one or more second type of actuators (1004) positioned at wrist locations of the robot; one or more third type of actuators (1006) positioned at the wrist locations of the robot; one or more fourth type of actuators (1008) positioned at elbow and ankle locations of the robot; one or more fifth type of actuators (1010) positioned at the torso location and the hip locations of the robot; and one or more sixth type of actuators (1012) positioned at knee locations and the hip locations of the robot.