[go: up one dir, main page]

Cosier et al., 2024 - Google Patents

A unifying variational framework for gaussian process motion planning

Cosier et al., 2024

View PDF
Document ID
11285141868705149933
Author
Cosier L
Iordan R
Zwane S
Franzese G
Wilson J
Deisenroth M
Terenin A
Bekiroglu Y
Publication year
Publication venue
International Conference on Artificial Intelligence and Statistics

External Links

Snippet

To control how a robot moves, motion planning algorithms must compute paths in high- dimensional state spaces while accounting for physical constraints related to motors and joints, generating smooth and stable motions, avoiding obstacles, and preventing collisions …
Continue reading at proceedings.mlr.press (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
    • G05—CONTROLLING; REGULATING
    • G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
    • G05B13/00—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion
    • G05B13/02—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric
    • G05B13/04—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric involving the use of models or simulators
    • 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
    • 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
    • G06N—COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N3/00—Computer systems based on biological models
    • G06N3/004—Artificial life, i.e. computers simulating life
    • G06N3/006—Artificial life, i.e. computers simulating life based on simulated virtual individual or collective life forms, e.g. single "avatar", social simulations, virtual worlds
    • 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
    • G05B17/00—Systems involving the use of models or simulators of said systems
    • G05B17/02—Systems involving the use of models or simulators of said systems electric
    • 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
    • G06F17/50—Computer-aided design
    • G06F17/5009—Computer-aided design using simulation
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T13/00—Animation
    • G06T13/20—3D [Three Dimensional] animation
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06N—COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N5/00—Computer systems utilising knowledge based models

Similar Documents

Publication Publication Date Title
Mukadam et al. Gaussian process motion planning
Aristidou et al. Inverse kinematics techniques in computer graphics: A survey
Polydoros et al. Survey of model-based reinforcement learning: Applications on robotics
Arruda et al. Uncertainty averse pushing with model predictive path integral control
Urain et al. Learning implicit priors for motion optimization
Doerr et al. Direct Loss Minimization Inverse Optimal Control.
Luo et al. Human intention inference and on-line human hand motion prediction for human-robot collaboration
Sacks et al. Learning sampling distributions for model predictive control
Liu et al. Collision-free motion generation based on stochastic optimization and composite signed distance field networks of articulated robot
Cosier et al. A unifying variational framework for gaussian process motion planning
Toussaint et al. A bayesian view on motor control and planning
Gopalakrishnan et al. Solving chance-constrained optimization under nonparametric uncertainty through hilbert space embedding
Nayak et al. Bidirectional sampling-based motion planning without two-point boundary value solution
Gaurav et al. Discriminatively learning inverse optimal control models for predicting human intentions
Liang et al. Simultaneous Multi-Robot Motion Planning with Projected Diffusion Models
Afzali et al. A modified convergence DDPG algorithm for robotic manipulation
Juelg et al. Fast online collision avoidance for mobile service robots through potential fields on 3D environment data processed on GPUs
Pavlasek et al. Ready, set, plan! planning to goal sets using generalized bayesian inference
Williams et al. Gpu based path integral control with learned dynamics
Ding et al. Safety-critical optimal control for robotic manipulators in a cluttered environment
Wüthrich et al. The coordinate particle filter-a novel particle filter for high dimensional systems
Sun et al. Dynamic Rank Adjustment in Diffusion Policies for Efficient and Flexible Training
Assouli et al. Initialization-driven neural generation and training for high-dimensional optimal control and first-order mean field games
Cai et al. Task2morph: Differentiable task-inspired framework for contact-aware robot design
Li et al. Global path guided model predictive path integral control: Applications to GPU-parallelizable robot simulation systems