Robot Manipulator Velocity Control with Low-DoF Teleoperation
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Solution Overview
Problem
Existing robotics technologies require highly customized and expensive hardware for controlling dexterous robot manipulators with many degrees-of-freedom, limiting usability and accessibility, and are inefficient in handling large action spaces during reinforcement learning-based tasks.
Innovation Solution
A method for controlling robot manipulators using a teleoperation device with fewer degrees-of-freedom, which involves formulating an optimization problem to determine joint velocities based on target velocities and constraints, allowing for effective control with a less complex input device and reducing computational resources.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If highly customized hardware is used to control dexterous robot manipulators with many degrees-of-freedom, then control precision and dexterity are improved, but hardware cost and complexity increase significantly
Solution Approach 1:
The patent introduces an optimization controller as an intermediary computational layer between the simplified input device and the robot manipulator. This controller solves optimization problems to translate low-DoF control inputs into appropriate joint velocity commands, enabling precise control without requiring complex hardware at the input device
Solution Approach 2:
The patent replaces complex mechanical control hardware with computational algorithms. Instead of using specialized hardware with many degrees of freedom to control each joint, the system uses optimization-based software control to map simplified user inputs to multi-DoF robot movements, substituting mechanical complexity with computational intelligence
2Ease of manufacture
If teleoperation device with fewer degrees-of-freedom is used, then hardware cost and accessibility are improved, but control capability for high-DoF manipulators deteriorates
Solution Approach 1:
The patent changes the control parameter space by formulating optimization problems that map from a reduced-dimensional input space to the full robot state space. The optimization controller dynamically adjusts control parameters based on task requirements, enabling a simplified device to control complex manipulators across diverse tasks
Solution Approach 2:
The optimization controller provides universal control capability that works across multiple tasks and robot configurations. The same simplified teleoperation device can control different high-DoF manipulators for various tasks by adjusting optimization parameters, achieving multi-functionality without hardware changes
3Measurement precision
If conventional control methods are used for reinforcement learning tasks, then training accuracy is improved, but computational resource consumption and training time increase
Solution Approach 1:
The patent extracts and separates the computational burden of high-DoF control from the reinforcement learning agent. By pre-computing optimization mappings and using efficient solvers, the system reduces the action space complexity that the RL agent must handle, allowing faster training while maintaining policy accuracy
Solution Approach 2:
The optimization controller performs preliminary computation to determine feasible joint velocities before execution. This pre-computation of control commands based on current state and desired task motion reduces real-time computational demands during RL training episodes, improving overall training efficiency
Data Source
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AI summary
Methods, systems, and apparatus, including computer programs encoded on computer storage media, for controlling a robot manipulator that has a plurality of joints. One of the methods includes obtaining a control input that comprises one or more velocity values that specify a target velocity of a reference point in a given coordinate frame; determining a respective joint velocity for each of the plurality of joints by generating a solution to an optimization problem formulated from the control input; and controlling the robot manipulator, including causing the plurality of joints of the robot manipulator to move in accordance with the respective joint velocities to approximate the control input.