Robotic Arm Navigation Using Self-Propelled Traction Control
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Solution Overview
Problem
Snake-like robotic arms face limitations in navigating complex and cluttered environments, particularly in confined spaces like gas turbine engines, due to their slender and flexible nature, which restricts their ability to self-propel and maintain traction effectively.
Innovation Solution
The implementation of a system comprising a flexible robotic arm with multiple degrees of freedom, coupled with sensors and an actuator, controlled by a machine learning model that uses environmental maps and operator instructions to self-propel and navigate through cluttered spaces using modes like sidewinding, corkscrewing, and inchworm movements, allowing the arm to automatically gain traction and adapt to complex paths.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If snake-like robotic arms are made slender and flexible to access confined spaces, then adaptability to complex environments is improved, but ability to self-propel and maintain traction deteriorates
Solution Approach 1:
The robotic arm is divided into multiple segments or modules that can independently actuate. Each segment has its own actuator, allowing distributed force generation along the arm's length. This segmentation enables the arm to maintain flexibility for accessing confined spaces while each segment contributes to self-propulsion through coordinated actuation, resolving the contradiction between slenderness and propulsion capability.
2Stability of the object's composition
If traditional robotic arms are used in cluttered environments, then structural stability is maintained, but navigation capability and reach into complex spaces deteriorates
Solution Approach 1:
The robotic arm transitions from a static, rigid structure to a dynamic, articulated system with multiple degrees of freedom. Each segment can independently change its configuration, allowing the arm to adapt its shape and posture for navigation through cluttered environments while maintaining structural integrity through controlled actuation. This dynamic capability enables both stability and enhanced navigation capability.
3Adaptability or versatility
If robotic arms have many degrees of freedom for complex navigation, then adaptability to cluttered environments is improved, but device complexity increases
Solution Approach 1:
Multiple functional components are merged into integrated modules. Each module combines actuation mechanisms, sensing capabilities, and structural elements into a unified unit. This merging reduces the overall system complexity by eliminating redundant components and simplifying control architecture, while still providing the necessary degrees of freedom for navigation in cluttered environments.
Data Source
AI summary
A robotic arm is inserted into a passage of a part to be examined. Operator instructions defining a tip motion for a tip of the robotic arm, sensor readings, and an environmental map are received. The operator instructions, the environmental map and sensor readings are applied to a previously trained machine learning model to produce control signals. The control signals to an actuator on the arm to control a movement of the robotic arm allowing the robotic arm to automatically gain traction in the passage and automatically move according to the movement.