Articulated Arm Torque Limiting for Mobile Base Stability
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Solution Overview
Problem
Robotic arms on mobile bases face challenges in maintaining stability of the robot base due to applied torques, especially in constrained environments, necessitating effective arm task planning to manage these forces and torques.
Innovation Solution
A computer-implemented method and system that generate a joint-torque-limit model based on allowable joint torque sets, adjusting requested joint torque sets to maintain base stability, using models and optimizers to project torque sets within allowable limits, and adjust for contact with external objects.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If the robotic arm applies high torques to perform tasks efficiently, then the productivity and task completion speed improve, but the stability of the robot base deteriorates
Solution Approach 1:
The system performs preliminary computation of a joint-torque-limit model before executing arm tasks. The model is pre-computed based on the robot's kinematic parameters, link masses, and desired base stability margins, enabling real-time torque limitation without compromising task performance. This preliminary preparation allows the arm to operate within stability-preserving torque bounds while maintaining high productivity.
Solution Approach 2:
The system dynamically adjusts arm joint torques by projecting requested torques onto the pre-computed joint-torque-limit model. When the arm interacts with external objects, the system modifies torque parameters in real-time by solving quadratic programs that respect the model constraints, thereby maintaining base stability while adapting to varying task requirements and external forces.
2Adaptability or versatility
If the robotic arm interacts with external objects to perform manipulation tasks, then the task functionality improves, but the risk of base destabilization increases
Solution Approach 1:
The system continuously monitors arm pose and requested joint torques, comparing them against the joint-torque-limit model. When the arm interacts with external objects, the feedback loop detects changes in required torques and adjusts them in real-time by projecting onto the limit model, ensuring that base stability constraints are never violated while maintaining full task functionality.
Solution Approach 2:
The joint-torque-limit model is computed dynamically based on the current arm configuration and base state. As the arm moves and interacts with external objects, the system re-evaluates and adjusts the torque limits in real-time, allowing the arm to adapt its torque application to maintain base stability while performing diverse manipulation tasks.
3Stability of the object's composition
If the system computes precise torque limitations in real-time, then the base stability control improves, but the computational complexity increases
Solution Approach 1:
The system pre-computes the joint-torque-limit model offline based on the robot's kinematic parameters, link masses, and desired stability margins. This preliminary computation transforms the complex real-time stability control problem into a simpler online projection problem, where only quadratic programs need to be solved during operation, significantly reducing real-time computational complexity while maintaining precise base stability control.
Solution Approach 2:
The control architecture is segmented into two distinct phases: offline model computation and online torque adjustment. The complex computational task of deriving the joint-torque-limit model is separated from the real-time control loop, allowing the online phase to focus only on projecting requested torques onto the pre-computed model using efficient quadratic programming, thereby reducing overall computational complexity.
Data Source
AI summary
A computer-implemented method includes generating a joint-torque-limit model for the articulated arm based on allowable joint torque sets corresponding to a base pose of the base. The method also include receiving a first requested joint torque set for a first arm pose of the articulated arm and determining, using the joint-torque-limit model, an optimized joint torque set corresponding to the first requested joint torque set. The method also includes receiving a second requested joint torque set for a second arm pose of the articulated arm and generating an adjusted joint torque set by adjusting the second requested joint torque set based on the optimized joint torque set. The method also includes sending the adjusted joint torque set to the articulated arm.