Search Results - "Tedrake, R"

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  1. 1

    Robot learning [TC Spotlight by Peters, J., Morimoto, J., Tedrake, R., Roy, N.

    Published in IEEE robotics & automation magazine (01-09-2009)
    “…Creating autonomous robots that can learn to act in unpredictable environments has been a long-standing goal of robotics, artificial intelligence, and the…”
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    Journal Article
  2. 2

    Robot learning [TC Spotlight] by Peters, J., Morimoto, J., Tedrake, R., Roy, N.

    Published in IEEE robotics & automation magazine (01-09-2009)
    “…Creating autonomous robots that can learn to act in unpredictable environments has been a long-standing goal of robotics, artificial intelligence, and the…”
    Get full text
    Journal Article
  3. 3

    Efficient Bipedal Robots Based on Passive-Dynamic Walkers by Collins, Steve, Ruina, Andy, Tedrake, Russ, Wisse, Martijn

    “…Passive-dynamic walkers are simple mechanical devices, composed of solid parts connected by joints, that walk stably down a slope. They have no motors or…”
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    Journal Article
  4. 4

    Path planning in 1000+ dimensions using a task-space Voronoi bias by Shkolnik, A., Tedrake, R.

    “…The reduction of the kinematics and/or dynamics of a high-DOF robotic manipulator to a low-dimension ldquotask spacerdquo has proven to be an invaluable tool…”
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    Conference Proceeding
  5. 5

    Stochastic policy gradient reinforcement learning on a simple 3D biped by Tedrake, R., Zhang, T.W., Seung, H.S.

    “…We present a learning system which is able to quickly and reliably acquire a robust feedback control policy for 3D dynamic walking from a blank-slate using…”
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    Conference Proceeding
  6. 6

    Actuating a simple 3D passive dynamic walker by Tedrake, R., Zhang, T.W., Ming-fai Fong, Seung, H.S.

    “…The passive dynamic walker described in this paper is a robot with a minimal number of degrees of freedom which is still capable of stable 3D dynamic walking…”
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    Conference Proceeding
  7. 7

    High-dimensional underactuated motion planning via task space control by Shkolnik, A., Tedrake, R.

    “…Kinodynamic planning algorithms have the potential to find feasible control trajectories which accomplish a task even in very nonlinear or constrained…”
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    Conference Proceeding
  8. 8

    Optimizing robust limit cycles for legged locomotion on unknown terrain by Hongkai Dai, Tedrake, R.

    “…While legged animals are adept at traversing rough landscapes, it remains a very challenging task for a legged robot to negotiate unknown terrain. Control…”
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    Conference Proceeding
  9. 9

    Motor control optimization of compliant one-legged locomotion in rough terrain by Iida, F., Tedrake, R.

    “…While underactuated robotic systems are capable of energy efficient and rapid dynamic behavior, we still do not fully understand how body dynamics can be…”
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    Conference Proceeding
  10. 10

    Reachability-guided sampling for planning under differential constraints by Shkolnik, A., Walter, M., Tedrake, R.

    “…Rapidly-exploring random trees (RRTs) are widely used to solve large planning problems where the scope prohibits the feasibility of deterministic solvers, but…”
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    Conference Proceeding
  11. 11

    Control synthesis and verification for a perching UAV using LQR-Trees by Moore, J., Tedrake, R.

    “…We consider the problem of designing a feedback controller for a fixed-wing unmanned aerial vehicle (UAV) to execute a dynamic post-stall maneuver and land…”
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    Conference Proceeding
  12. 12

    Collision Detection in Legged Locomotion using Supervised Learning by Doshi, F., Brunskill, E., Shkolnik, A., Kollar, T., Rohanimanesh, K., Tedrake, R., Roy, N.

    “…We propose a fast approach for detecting collision- free swing-foot trajectories for legged locomotion over extreme terrains. Instead of simulating the swing…”
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    Conference Proceeding
  13. 13

    Approximate optimal control of the compass gait on rough terrain by Byl, K., Tedrake, R.

    “…In this paper, we explore the capabilities of actuated models of the compass gait walker on rough terrain. We solve for the optimal high-level feedback policy…”
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    Conference Proceeding
  14. 14

    Safety verification of reactive controllers for UAV flight in cluttered environments using barrier certificates by Barry, A. J., Majumdar, A., Tedrake, R.

    “…Unmanned aerial vehicles (UAVs) have a so-far untapped potential to operate at high speeds through cluttered environments. Many of these systems are limited by…”
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    Conference Proceeding
  15. 15

    On the controllability of fixed-wing perching by Roberts, J.W., Cory, R., Tedrake, R.

    Published in 2009 American Control Conference (01-06-2009)
    “…The ability of birds to perch robustly and effectively is a powerful demonstration of the capabilities of nature's control systems. Their apparent robustness…”
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    Conference Proceeding
  16. 16

    Inverse Kinematics for a Point-Foot Quadruped Robot with Dynamic Redundancy Resolution by Shkolnik, A., Tedrake, R.

    “…In this work we examine the control of center of mass and swing leg trajectories in LittleDog, a point-foot quadruped robot. It is not clear how to formulate a…”
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    Conference Proceeding
  17. 17

    Region of attraction estimation for a perching aircraft: A Lyapunov method exploiting barrier certificates by Glassman, E., Desbiens, A. L., Tobenkin, M., Cutkosky, M., Tedrake, R.

    “…Dynamic perching maneuvers for fixed-wing aircraft are becoming increasingly plausible due to recent progress in perching using `micro-spines' mounted on tuned…”
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    Conference Proceeding
  18. 18

    Non-Gaussian belief space planning: Correctness and complexity by Platt, R., Kaelbling, L., Lozano-Perez, T., Tedrake, R.

    “…We consider the partially observable control problem where it is potentially necessary to perform complex information-gathering operations in order to localize…”
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    Conference Proceeding
  19. 19

    Algebraic verification for parameterized motion planning libraries by Majumdar, A., Tobenkin, M., Tedrake, R.

    Published in 2012 American Control Conference (ACC) (01-06-2012)
    “…Recent progress in algorithms for estimating regions of attraction and invariant sets of nonlinear systems has led to the application of these techniques to…”
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    Conference Proceeding
  20. 20

    Convex optimization in identification of stable non-linear state space models by Tobenkin, M M, Manchester, I R, Wang, J, Megretski, A, Tedrake, R

    “…A new framework for nonlinear system identification is presented in terms of optimal fitting of stable nonlinear state space equations to input/output/state…”
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    Conference Proceeding