Sergey Levine

Office & Mailing Address:

Gates Building, Room 286

353 Serra Mall

Stanford, CA 94305

Email:

Curriculum Vitae:

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This paper presents an inverse reinforcement learning algorithm for learning unknown nonlinear reward functions. The algorithm uses Gaussian processes and a probabilistic model of the expert to capture complex behaviors from suboptimal stochastic demonstrations, while automatically balancing the simplicity of the learned reward structure against its consistency with the observed actions.

In this article, we present a method for efficiently synthesizing animations for characters traversing complex dynamic environments by sequencing parameterized locomotion controllers using space-time planning. The controllers are created from motion capture data, and the space-time planner determines the optimal sequence of controllers to reach a goal in a dynamic, changing environment.

This paper presents an algorithm for learning an unknown reward function for a Markov decision process when good basis features are not available, using example traces from the MDP's optimal policy. The algorithm constructs reward features from a large collection of component features, by building logical conjunctions of those component features that are relevant to the example policy.

Gesture controllers learn optimal policies to generate smooth, compelling gesture animations from speech and other optional inputs. The accompanying video presents examples of various controllers, including controllers that recognize key words, admit manual manipulation of gesture style, and even animate a character with a non-humanoid morphology.

This paper presents the body language synthesis system described in my undergraduate thesis. The method automatically synthesizes body language animations directly from the participants' speech signals, without the need for additional input. The body language animations are synthesized by selecting segments from motion capture data of real people in conversation in real time.

In this report, I describe a new approach for synthesizing body language from prosody using a set of intermediate motion parameters that can be used to describe stylistic qualities of gesture independent of their form. The quality of synthesized motion parameters is compared to the parameters of the original motions accompanying an utterance to obtain a quantitative measure of the performance of the method.

In my undergraduate thesis, I describe the body language synthesis system. This system generates believable body language animations from live speech input, using only the prosody of the speaker's voice. Since the method is suitable for live speech, it can be used in interactive applications, such as networked virtual worlds.

Rendering the Eagle Nebula

My project for Pat Hanrahan's CS 348B rendering class, completed in collaboration with Edward Luong, received the Grand Prize in the rendering competition. The image is of the Eagle Nebula. The rendering used volumetric photon mapping and simulated the excitement of gases in the nebula by ultraviolet radiation, and the resulting emission of lower-wavelength light.

Airship Combat

My project for Marc Levoy's introductory computer graphics course received the "most creative" award in the final project competition. The project is a game that allows players to control sail-powered airships armed with cannons. The game simulates the physics of the sails using a simple explicit Euler scheme, and uses hierarchical collision detection to detect hits.

Nali Chronicles

Nali Chronicles is a mod for Unreal Tournament that I developed with a group of friends around 2001-2005. All of the programming, most of the art assets, and some of the level design was done by me. The game is a little outdated by now, but if you have a copy of the original Unreal Tournament, you can download the installer and give it a go.