Identification of Compliant Contact Parameters and Admittance Force Modulation on a Non-stationary Compliant Surface
April 21, 2020 Β· Declared Dead Β· π IEEE International Conference on Robotics and Automation
"No code URL or promise found in abstract"
Evidence collected by the PWNC Scanner
Authors
Lasitha Wijayarathne, Frank L. Hammond
arXiv ID
2004.09729
Category
cs.RO: Robotics
Citations
2
Venue
IEEE International Conference on Robotics and Automation
Last Checked
4 months ago
Abstract
Although autonomous control of robotic manipulators has been studied for several decades, they are not commonly used in safety-critical applications due to lack of safety and performance guarantees - many of them concerning the modulation of interaction forces. This paper presents a mechanical probing strategy for estimating the environmental impedance parameters of compliant environments, independent a manipulator's controller design, and configuration. The parameter estimates are used in a position-based adaptive force controller to enable control of interaction forces in compliant, stationary, and non-stationary environments. This approach is targeted for applications where the workspace is constrained and non-stationary, and where force control is critical to task success. These applications include surgical tasks involving manipulation of compliant, delicate, moving tissues. Results show fast parameter estimation and successful force modulation that compensates for motion.
Community Contributions
Found the code? Know the venue? Think something is wrong? Let us know!
π Similar Papers
In the same crypt β Robotics
R.I.P.
π»
Ghosted
R.I.P.
π»
Ghosted
AirSim: High-Fidelity Visual and Physical Simulation for Autonomous Vehicles
π
π
The Cartographer
A Survey of Motion Planning and Control Techniques for Self-driving Urban Vehicles
π
π
The Cartographer
Unmanned Aerial Vehicles: A Survey on Civil Applications and Key Research Challenges
π
π
The Cartographer
A Survey of Autonomous Driving: Common Practices and Emerging Technologies
R.I.P.
π»
Ghosted
Learning agile and dynamic motor skills for legged robots
Died the same way β π» Ghosted
R.I.P.
π»
Ghosted
Federated Learning: Strategies for Improving Communication Efficiency
R.I.P.
π»
Ghosted
In-Datacenter Performance Analysis of a Tensor Processing Unit
R.I.P.
π»
Ghosted
Deep Convolutional Neural Networks for Computer-Aided Detection: CNN Architectures, Dataset Characteristics and Transfer Learning
R.I.P.
π»
Ghosted