Stochastic differential equations (3rd ed.): an introduction with applications
Stochastic differential equations (3rd ed.): an introduction with applications
Spacetime constraints revisited
SIGGRAPH '93 Proceedings of the 20th annual conference on Computer graphics and interactive techniques
SIGGRAPH '95 Proceedings of the 22nd annual conference on Computer graphics and interactive techniques
Limit cycle control and its application to the animation of balancing and walking
SIGGRAPH '96 Proceedings of the 23rd annual conference on Computer graphics and interactive techniques
Adapting simulated behaviors for new characters
Proceedings of the 24th annual conference on Computer graphics and interactive techniques
Physically based motion transformation
Proceedings of the 26th annual conference on Computer graphics and interactive techniques
SIGGRAPH '88 Proceedings of the 15th annual conference on Computer graphics and interactive techniques
Motion interpolation by optimal control
SIGGRAPH '88 Proceedings of the 15th annual conference on Computer graphics and interactive techniques
Composable controllers for physics-based character animation
Proceedings of the 28th annual conference on Computer graphics and interactive techniques
Motion capture-driven simulations that hit and react
Proceedings of the 2002 ACM SIGGRAPH/Eurographics symposium on Computer animation
Introduction to Reinforcement Learning
Introduction to Reinforcement Learning
Dynamic Programming
Apprenticeship learning via inverse reinforcement learning
ICML '04 Proceedings of the twenty-first international conference on Machine learning
ACM SIGGRAPH 2004 Papers
Fluid control using the adjoint method
ACM SIGGRAPH 2004 Papers
Synthesizing physically realistic human motion in low-dimensional, behavior-specific spaces
ACM SIGGRAPH 2004 Papers
Adaptation of performed ballistic motion
ACM Transactions on Graphics (TOG)
Learning physics-based motion style with nonlinear inverse optimization
ACM SIGGRAPH 2005 Papers
Responsive characters from motion fragments
ACM SIGGRAPH 2007 papers
Near-optimal character animation with continuous control
ACM SIGGRAPH 2007 papers
TRACKS: toward directable thin shells
ACM SIGGRAPH 2007 papers
SIMBICON: simple biped locomotion control
ACM SIGGRAPH 2007 papers
Simulating biped behaviors from human motion data
ACM SIGGRAPH 2007 papers
Continuation methods for adapting simulated skills
ACM SIGGRAPH 2008 papers
Interactive simulation of stylized human locomotion
ACM SIGGRAPH 2008 papers
Dynamic Programming and Optimal Control, Vol. II
Dynamic Programming and Optimal Control, Vol. II
Synthesis of constrained walking skills
ACM SIGGRAPH Asia 2008 papers
Real-time control of physically based simulations using gentle forces
ACM SIGGRAPH Asia 2008 papers
Robust task-based control policies for physics-based characters
ACM SIGGRAPH Asia 2009 papers
ACM SIGGRAPH 2010 papers
Composite control of physically simulated characters
ACM Transactions on Graphics (TOG)
Displacement interpolation using Lagrangian mass transport
Proceedings of the 2011 SIGGRAPH Asia Conference
Discovery of complex behaviors through contact-invariant optimization
ACM Transactions on Graphics (TOG) - SIGGRAPH 2012 Conference Proceedings
Terrain runner: control, parameterization, composition, and planning for highly dynamic motions
ACM Transactions on Graphics (TOG) - Proceedings of ACM SIGGRAPH Asia 2012
Interactive Character Animation Using Simulated Physics: A State-of-the-Art Review
Computer Graphics Forum
Control of rotational dynamics for ground behaviors
Proceedings of the 12th ACM SIGGRAPH/Eurographics Symposium on Computer Animation
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Controllers are necessary for physically-based synthesis of character animation. However, creating controllers requires either manual tuning or expensive computer optimization. We introduce linear Bellman combination as a method for reusing existing controllers. Given a set of controllers for related tasks, this combination creates a controller that performs a new task. It naturally weights the contribution of each component controller by its relevance to the current state and goal of the system. We demonstrate that linear Bellman combination outperforms naive combination often succeeding where naive combination fails. Furthermore, this combination is provably optimal for a new task if the component controllers are also optimal for related tasks. We demonstrate the applicability of linear Bellman combination to interactive character control of stepping motions and acrobatic maneuvers.