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Simulation Tools for Model-Based Robotics: Comparison of ...
Simulation Tools for Model-Based Robotics: Comparison of Bullet, Havok, MuJoCo, ODE and PhysX Tom Erez, Yuval Tassa and Emanuel Todorov. Abstract—There is growing need for software tools that can accurately simulate the complex dynamics of modern robots. While a number of candidates exist, the field is fragmented.
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Particle Filters - University of Washington
homes.cs.washington.eduExample 3: Example Particle Distributions [Grisetti, Stachniss, Burgard, T-RO2006] Particles generated from the approximately optimal proposal distribution. If using the standard motion model, in all three cases the particle set would have been similar to (c). "
Chapter 14 Proposed Systems - University of Washington
homes.cs.washington.eduIn the late 1960s TSO was being developed as a timesharing subsys- tem for IBM’s batch-oriented MVT operating system. During final design and initial implementation of the final system, an earlier prototype was measured in a test environment, and a queueing network model was
Evaluating&improving fault localization techniques
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Game Theory, Alive - University of Washington
homes.cs.washington.eduAcknowledgements We are grateful to Alan Hammond, Yun Long, G abor Pete, and Peter Ralph for scribing early drafts of some of the chapters in this book from lectures by Yuval
Chapter 3 Fundamental Laws - University of Washington
homes.cs.washington.edu3.3. Little’s Law Hence: 43 Little’s Law: N = XR That is, the average number of requests in a system is equal to the pro- duct of the throughput of that system and the average time spent in that
Sloth: Locating Sites for Repetitive Edits with Lazy ...
homes.cs.washington.eduSloth: Locating Sites for Repetitive Edits with Lazy Concrete Pattern Matching on Trees Conference’17, July 2017, Washington, DC, USA matches on any identifier but ignores what construct the identifier
Identification and control of a pneumatic robot
homes.cs.washington.eduIdentification and control of a pneumatic robot Emanuel Todorov 1,ChunyanHu, Alex Simpkins1 and Javier Movellan2 1Applied Mathematics and Computer Science and Engineering, University of Washington 2 Institute for Neural Computation, University of California San Diego Abstract—Pneumatic actuators have a number of advantages over electric motors, including strength-to-weight ratio, tunable
Policy Gradient Methods for Reinforcement Learning with ...
homes.cs.washington.eduWilliams’s (1988, 1992) REINFORCE algorithm also flnds an unbiased estimate of the gradient, but without the assistance of a learned value function. REINFORCE learns much more slowly than RL methods using value functions and has received relatively little attention. Learning a value function and using it to reduce the variance
Jacobian methods for inverse kinematics and planning
homes.cs.washington.eduOperating Principle: - Project difference vector Dx on those dimensions q which can reduce it ... Equality constraints Such constraints restrict the state to a manifold. If the simple push-towards-the-goal action projected on the manifold always gets us closer to the goal, then the problem is …
Optimal Control Theory - homes.cs.washington.edu
homes.cs.washington.eduEquations (1, 3, 4) generalize to the stochastic case in the same way as equation (2) does. An optimal control problem with discrete states and actions and probabilistic state transitions is called a Markov decision process (MDP).
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