[go: up one dir, main page]

Huang et al., 2024 - Google Patents

Diffusionseeder: Seeding motion optimization with diffusion for rapid motion planning

Huang et al., 2024

View PDF
Document ID
18390465273052660424
Author
Huang H
Sundaralingam B
Mousavian A
Murali A
Goldberg K
Fox D
Publication year
Publication venue
arXiv preprint arXiv:2410.16727

External Links

Snippet

Running optimization across many parallel seeds leveraging GPU compute have relaxed the need for a good initialization, but this can fail if the problem is highly non-convex as all seeds could get stuck in local minima. One such setting is collision-free motion optimization …
Continue reading at arxiv.org (PDF) (other versions)

Classifications

    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06N—COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N99/00—Subject matter not provided for in other groups of this subclass
    • G06N99/005—Learning machines, i.e. computer in which a programme is changed according to experience gained by the machine itself during a complete run
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06K—RECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
    • G06K9/00—Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
    • G06K9/62—Methods or arrangements for recognition using electronic means
    • G06K9/6267—Classification techniques
    • G06K9/6268—Classification techniques relating to the classification paradigm, e.g. parametric or non-parametric approaches
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06K—RECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
    • G06K9/00—Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
    • G06K9/62—Methods or arrangements for recognition using electronic means
    • G06K9/6217—Design or setup of recognition systems and techniques; Extraction of features in feature space; Clustering techniques; Blind source separation
    • G06K9/6232—Extracting features by transforming the feature space, e.g. multidimensional scaling; Mappings, e.g. subspace methods
    • G06K9/6247—Extracting features by transforming the feature space, e.g. multidimensional scaling; Mappings, e.g. subspace methods based on an approximation criterion, e.g. principal component analysis
    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
    • G05B2219/00—Program-control systems
    • G05B2219/30—Nc systems
    • G05B2219/39—Robotics, robotics to robotics hand
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06N—COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N3/00—Computer systems based on biological models
    • G06N3/02—Computer systems based on biological models using neural network models
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06F—ELECTRICAL DIGITAL DATA PROCESSING
    • G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
    • G06F17/10—Complex mathematical operations
    • G06F17/11—Complex mathematical operations for solving equations, e.g. nonlinear equations, general mathematical optimization problems
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06F—ELECTRICAL DIGITAL DATA PROCESSING
    • G06F19/00—Digital computing or data processing equipment or methods, specially adapted for specific applications
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00—Image analysis

Similar Documents

Publication Publication Date Title
Qureshi et al. Motion planning networks
Shi et al. Waypoint-based imitation learning for robotic manipulation
EP3837641B1 (en) Deep reinforcement learning-based techniques for end to end robot navigation
Das et al. Learning-based proxy collision detection for robot motion planning applications
Huang et al. Diffusionseeder: Seeding motion optimization with diffusion for rapid motion planning
Han et al. Deep reinforcement learning for robot collision avoidance with self-state-attention and sensor fusion
Finn et al. Deep visual foresight for planning robot motion
Mukadam et al. Gaussian process motion planning
Simeonov et al. A long horizon planning framework for manipulating rigid pointcloud objects
EP3739418B1 (en) Method of controlling a vehicle and apparatus for controlling a vehicle
US20180032868A1 (en) Early prediction of an intention of a user's actions
Park et al. Fast and bounded probabilistic collision detection for high-DOF trajectory planning in dynamic environments
Chen et al. Catnips: Collision avoidance through neural implicit probabilistic scenes
Li et al. Representing robot geometry as distance fields: Applications to whole-body manipulation
Li et al. Configuration space distance fields for manipulation planning
Toussaint et al. A bayesian view on motor control and planning
Ochi et al. Deep learning scooping motion using bilateral teleoperations
CN116149171A (en) Methods of Controlling Proxies
Liu et al. Review on motion planning of robotic manipulator in dynamic environments
Zhu et al. Should we learn contact-rich manipulation policies from sampling-based planners?
Park et al. Fast and bounded probabilistic collision detection in dynamic environments for high-dof trajectory planning
Kwon et al. Conformalized reachable sets for obstacle avoidance with spheres
Kasaei et al. A data-efficient neural ODE framework for optimal control of soft manipulators
Sintov et al. Motion planning with competency-aware transition models for underactuated adaptive hands
Deshpande et al. An algorithm to create model file for Partially Observable Markov Decision Process for mobile robot path planning