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Classical motion planning for robotic manipulation includes a set of general algorithms that aim to minimize a scene-specific cost of executing a given plan.
“A Formal Basis for the Heuristic Determination of Minimum Cost Paths”
Peter. Hart, Nils. Nilsson and Bertram Raphael · 1968
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“Rapidly-exploring random trees : a new tool for path planning”
Steven. LaValle · 1998
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“RRT-connect: An efficient approach to single-query path planning”
James. Kuffner and Steven. LaValle · 2000
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“Proximity queries and penetration depth computation on 3d game objects”, 2001
Gino Bergen · 2001
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“ARA*: Anytime A* with Provable Bounds on Sub-Optimality.”
Maxim Likhachev, Geoffrey. Gordon and Sebastian Thrun · 2003
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“Anytime Dynamic A*: An Anytime, Replanning Algorithm.”
Maxim Likhachev et al · 2005
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“CHOMP: Gradient optimization techniques for efficient motion planning”
Nathan Ratliff, Matt Zucker, J. Bagnell and Siddhartha Srinivasa · 2009
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“Geometric Fabrics for the Acceleration-based Design of Robotic Motion”, 2021
Mandy Xie et al · 2010
Earlier work this paper cites.
“The Open Motion Planning Library”
Ioan. Sucan, Mark Moll and Lydia. Kavraki · 2012
Earlier work this paper cites.
“Finding Locally Optimal, Collision-Free Trajectories with Sequential Convex Optimization”, 2013
John Schulman et al · 2013
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“An integrated system for real-time model predictive control of humanoid robots”
Tom Erez et al · 2013
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“Real-Time Model Predictive Control for Quadrotors”
Moses Bangura · 2014
Earlier work this paper cites.
“Generative Adversarial Networks”, 2014
Ian. Goodfellow et al · 2014
Earlier work this paper cites.
“Model Predictive Path Integral Control using Covariance Variable Importance Sampling”
Grady Williams, Andrew Aldrich and Evangelos. Theodorou · 2015
Earlier work this paper cites.
“Deep unsupervised learning using nonequilibrium thermodynamics”
Jascha Sohl-Dickstein, Eric Weiss, Niru Maheswaranathan and Surya Ganguli · 2015
Cited alongside, same era.
“Aggressive driving with model predictive path integral control”
Grady Williams et al · 2016
Cited alongside, same era.
“An algorithmic perspective on imitation learning”
Takayuki Osa et al · 2018
Cited alongside, same era.
“Motion Planning Networks”
Ahmed. Qureshi, Anthony Simeonov, Mayur. Bency and Michael. Yip · 2019
Cited alongside, same era.
“Denoising diffusion probabilistic models”
Jonathan Ho, Ajay Jain and Pieter Abbeel · 2020
Cited alongside, same era.
“Adaptively Informed Trees (AIT): Fast Asymptotically Optimal Path Planning through Adaptive Heuristics”
Marlin Strub and Jonathan Gammell · 2020
Cited alongside, same era.
“Hierarchical text-conditional image generation with clip latents”
Aditya Ramesh et al · 2022
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“Photorealistic text-to-image diffusion models with deep language understanding”
Chitwan Saharia et al · 2022
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“Planning with diffusion for flexible behavior synthesis”
Michael Janner, Yilun Du, Joshua Tenenbaum and Sergey Levine · 2022
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“Is conditional generative modeling all you need for decision-making?”
Anurag Ajay et al · 2022
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“Auto-Encoding Variational Bayes”, 2022
Diederik Kingma and Max Welling · 2022
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“Object rearrangement using learned implicit collision functions”
Michael Danielczuk, Arsalan Mousavian, Clemens Eppner and Dieter Fox · 2021
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“Zero-shot text-to-image generation”
Aditya Ramesh et al · 2021
Cited alongside, same era.
“Diffusion Models Beat GANs on Image Synthesis”, 2021
Prafulla Dhariwal and Alex Nichol · 2021
Cited alongside, same era.
“PyBullet, a Python module for physics simulation for games, robotics and machine learning”, http://pybullet.org , 2016–2021
Erwin Coumans and Yunfei Bai · 2021
Cited alongside, same era.
“Approaches and challenges in robotic perception for table-top rearrangement and planning”
Aditya Agarwal et al · 2022
Cited alongside, same era.
“Storm: An integrated framework for fast joint-space model-predictive control for reactive manipulation”
Mohak Bhardwaj et al · 2022
Cited alongside, same era.
Later among the works it cites.
“Motion policy networks”
Adam Fishman et al · 2023
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“Imitating human behaviour with diffusion models”
Tim Pearce et al · 2023
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“Learning fine-grained bimanual manipulation with low-cost hardware”
Tony Zhao, Vikash Kumar, Sergey Levine and Chelsea Finn · 2023
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“Mm-diffusion: Learning multi-modal diffusion models for joint audio and video generation”
Ludan Ruan et al · 2023
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“Diffusion policy: Visuomotor policy learning via action diffusion”
Cheng Chi et al · 2023
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“AdaptDiffuser: Diffusion Models as Adaptive Self-evolving Planners”, 2023
Zhixuan Liang et al · 2023
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“Motion Planning Diffusion: Learning and Planning of Robot Motions with Diffusion Models”
Joao Carvalho et al · 2023
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“A fast procedure for computing the distance between complex objects in three-dimensional space”
E.G. Gilbert, D.W. Johnson and S.S. Keerthi · 2083
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