Robot Programming by Kinesthetic Demonstration Without External Sensors
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing methods for programming robots are costly, time-consuming, and require extensive user expertise, especially for complex movements, and often necessitate external hardware, limiting their applicability in real industrial contexts where rapid changes and precise control are needed.
Innovation Solution
A method that utilizes kinesthetic teaching without external sensing modules, allowing a single user demonstration to generate a robot control program by recording joint positions and velocities, with adjustable parameters for modifying the program, enabling in-situ programming and reducing operator burden in three-dimensional guidance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional numerical programming or GUI-based teaching methods are used, then the robot can be programmed to perform complex movements, but the programming process becomes time-consuming and requires extensive user expertise
Solution Approach 1:
The system captures the operator's natural demonstration movements using sensing devices and directly copies these movements to generate robot control programs. This eliminates the need for traditional numerical programming or GUI-based point-by-point teaching, reducing programming time while maintaining accuracy through direct motion capture and processing of joint position/velocity data.
Solution Approach 2:
The invention replaces manual GUI operations and traditional teaching methods with an automated sensing and processing system. The robot's built-in sensors capture demonstration movements, and automated algorithms process the joint position and velocity data to generate control programs, substituting mechanical teaching operations with automated electronic sensing and computation.
2Ease of operation
If external sensing modules or hardware (such as magnetic trackers, gloves, cameras, full-body sensing suits) are used for programming by demonstration, then the robot can learn tasks more intuitively, but the cost and complexity of deployment increases greatly
Solution Approach 1:
The robot system performs multiple functions using its existing components: it operates as both an actuator and a measuring device. The robot's built-in joint position and velocity sensors, originally designed for control, are repurposed to capture demonstration movements for programming, eliminating the need for external sensing hardware while maintaining programming intuitiveness.
Solution Approach 2:
The robot programs itself by capturing its own demonstration movements through its built-in sensing capabilities. The system uses its own joint position and velocity sensors to record the operator's natural movements and automatically processes this data into control programs, making the robot self-sufficient and eliminating dependency on external hardware.
3Manufacturing precision
If multiple user demonstrations are required to extract a usable program representation, then the program can be more accurate, but the programming process becomes more time-consuming and complex
Solution Approach 1:
The system processes joint position and velocity data from demonstrations in real-time, using automated algorithms to extract via-points and generate control programs. The feedback mechanism allows the system to process demonstration data efficiently, achieving accurate program representation from fewer demonstrations by leveraging automated data processing and motion analysis algorithms.
Solution Approach 2:
The invention changes the parameters used for program extraction from requiring multiple full demonstrations to extracting usable programs from fewer demonstrations by processing joint position and velocity data. The system transforms raw sensor data into meaningful control parameters through automated algorithms, improving programming efficiency while maintaining program accuracy.
4Measurement precision
If the operator manually guides the robot through desired motions using gravity-compensation mode, then the robot can learn the intended path, but the operator must maintain control in three or more dimensions which is complex and time-consuming
Solution Approach 1:
Instead of requiring the operator to manually guide the robot through complex multi-dimensional motions, the system captures the operator's natural demonstration movements and copies them directly. The sensing devices record joint position and velocity data, and the robot reproduces these movements automatically, eliminating the difficulty of manual three-dimensional control while maintaining motion path accuracy.
Solution Approach 2:
The invention replaces manual mechanical guidance operations with automated sensing and reproduction. The robot's control system processes captured demonstration data and automatically generates control programs, substituting the operator's manual three-dimensional control efforts with automated electronic processing and motion reproduction.
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
This approach simplifies and accelerates robot programming, allowing efficient and automated teaching of motions, making frequent programming feasible for small batch jobs and reducing complexity by eliminating the need for external hardware and minimizing operator effort.
Implementation Method 1
sensors for measuring joint positions and velocities in each of its joints
Implementation Method 2
sensors for measuring joint positions and velocities in each of its joints
Data Source
AI summary
There is provided a method and computer program product for programming a robot by manually operating it in gravity-compensation kinesthetic-guidance mode. More specifically there is provided method and computer program product that uses kinesthetic teaching as a demonstration input modality and does not require the installation or use of any external sensing or data-capturing modules. It requires a single user demonstration to extract a representation of the program, and presents the user with a series of easily-controllable parameters that allow them to modify or constrain the parameters of the extracted program representation of the task.