Sampling constrained trajectories using composable diffusion models
Trajectory optimization and optimal control are powerful tools for synthesizing complex robot
behavior using appropriate cost functions and constraints. However, methods for solving the …
behavior using appropriate cost functions and constraints. However, methods for solving the …
Safe Reinforcement Learning on the Constraint Manifold: Theory and Applications
Integrating learning-based techniques, especially reinforcement learning, into robotics is
promising for solving complex problems in unstructured environments. However, most …
promising for solving complex problems in unstructured environments. However, most …
Physics-informed Neural Motion Planning on Constraint Manifolds
R Ni, AH Qureshi - arXiv preprint arXiv:2403.05765, 2024 - arxiv.org
Constrained Motion Planning (CMP) aims to find a collision-free path between the given
start and goal configurations on the kinematic constraint manifolds. These problems appear …
start and goal configurations on the kinematic constraint manifolds. These problems appear …
PINSAT: Parallelized Interleaving of Graph Search and Trajectory Optimization for Kinodynamic Motion Planning
Trajectory optimization is a widely used technique in robot motion planning for letting the
dynamics and constraints on the system shape and synthesize complex behaviors. Several …
dynamics and constraints on the system shape and synthesize complex behaviors. Several …
Neural Randomized Planning for Whole Body Robot Motion
Robot motion planning has made vast advances over the past decades, but the challenge
remains: robot mobile manipulators struggle to plan long-range whole-body motion in …
remains: robot mobile manipulators struggle to plan long-range whole-body motion in …
Zero-Shot Constrained Motion Planning Transformers Using Learned Sampling Dictionaries
JJ Johnson, AH Qureshi, MC Yip - 2024 IEEE International …, 2024 - ieeexplore.ieee.org
Constrained robot motion planning is a ubiquitous need for robots interacting with everyday
environments, but it is a notoriously difficult problem to solve. Many sampled points in a …
environments, but it is a notoriously difficult problem to solve. Many sampled points in a …
Bridging the gap between Learning-to-plan, Motion Primitives and Safe Reinforcement Learning
Trajectory planning under kinodynamic constraints is fundamental for advanced robotics
applications that require dexterous, reactive, and rapid skills in complex environments …
applications that require dexterous, reactive, and rapid skills in complex environments …
Topology-preserved distorted space path planning
Y Xie, Q Yang, R Zhou, Z Cao, H Shi - Industrial Robot: the …, 2024 - emerald.com
Purpose Fast obstacle avoidance path planning is a challenging task for multijoint robots
navigating through cluttered workspaces. This paper aims to address this issue by …
navigating through cluttered workspaces. This paper aims to address this issue by …
Energy-based Contact Planning under Uncertainty for Robot Air Hockey
Planning robot contact often requires reasoning over a horizon to anticipate outcomes,
making such planning problems computationally expensive. In this letter, we propose a …
making such planning problems computationally expensive. In this letter, we propose a …
Boosting Machine Learning Techniques with Positional Encoding for Robot Collision Checking
Self-collision checking plays an important role in robot motion planning. In sampling-based
motion planning methods, collision checking is performed multiple times, so this procedure …
motion planning methods, collision checking is performed multiple times, so this procedure …