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This paper describes the pragmatic design and construction of geometric fabrics for shaping a robot's task-independent nominal behavior, capturing behavioral components such as obstacle avoidance, joint limit avoidance, redundancy resolution, global navigation heuristics, etc.
Multi-objective policy generation for multi-robot systems using riemannian motion policies
Anqi Li, Mustafa Mukadam, Magnus Egerstedt, and Byron Boots · 1902
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A unified approach for motion and force control of robot manipulators: The operational space formulation
O. Khatib · 1987
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Geometric control of mechanical systems: modeling, analysis, and design for simple mechanical control systems , volume 49
Francesco Bullo and Andrew D Lewis · 2004
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Planning Algorithms
Steven M. LaValle · 2006
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A unifying framework for robot control with redundant DOFs
Jan Peters, Michael Mistry, Firdaus Udwadia, Jun Nakanishi, and Stefan Schaal · 2008
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Optimization fabrics for behavioral design
Nathan D. Ratliff, Karl Van Wyk, Mandy Xie, Anqi Li, and Asif Muhammad Rana · 2010
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Introduction to Smooth Manifolds
John M. Lee · 2012
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An integrated system for real-time model-predictive control of humanoid robots
Tom Erez, Kendall Lowrey, Yuval Tassa, Vikash Kumar, Svetoslav Kolev, and Emanuel Todorov · 2013
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An autonomous manipulation system based on force control and optimization
L. Righetti, M. Kalakrishnan, P. Pastor, J. Binney, J. Kelly, R. Voorhies, G. Sukhatme, and S. Schaal · 2013
Cited alongside, same era.
Understanding the geometry of workspace obstacles in motion optimization
Nathan Ratliff, Marc Toussaint, and Stefan Schaal · 2015
Cited alongside, same era.
Real-time perception meets reactive motion generation
Daniel Kappler, Franziska Meier, Jan Issac, Jim Mainprice, Cristina Garcia Cifuentes, Manuel Wüthrich, Vincent Berenz, Stefan Schaal, Nathan Ratliff, and Jeannette Bohg · 2018
Cited alongside, same era.
Continuous-time Gaussian process motion planning via probabilistic inference
Mustafa Mukadam, Jing Dong, Xinyan Yan, Frank Dellaert, and Byron Boots · 2018
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Nathan D Ratliff, Jan Issac, Daniel Kappler, Stan Birchfield, and Dieter Fox · 2018
Later among the works it cites.
Riemannian motion policy fusion through learnable lyapunov function reshaping
Mustafa Mukadam, Ching-An Cheng, Dieter Fox, Byron Boots, and Nathan Ratliff · 2019
Later among the works it cites.
Learning reactive motion policies in multiple task spaces from human demonstrations
M Asif Rana, Anqi Li, Harish Ravichandar, Mustafa Mukadam, Sonia Chernova, Dieter Fox, Byron Boots, and Nathan Ratliff · 2019
Later among the works it cites.
Generalized nonlinear and finsler geometry for robotics
Nathan D. Ratliff, Karl Van Wyk, Mandy Xie, Anqi Li, and Asif Muhammad Rana · 2021
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RMPflow: A computational graph for automatic motion policy generation
C.-A. Cheng, Mustafa Mukadam, Jan Issac, Stan Birchfield, Dieter Fox, Byron Boots, and Nathan Ratliff
Cited in the paper.
Rmpflow: A computational graph for automatic motion policy generation
Ching-An Cheng, Mustafa Mukadam, Jan Issac, Stan Birchfield, Dieter Fox, Byron Boots, and Nathan Ratliff
Cited in the paper.