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Whole-Body Motion for Wheeled Humanoid Robots

Optimizing the control of articulated mobile robots leads to emergent behaviors that improve the effectiveness, efficiency and stability of wheeled humanoids and dynamically stable mobile manipulators. Our simulated results show that optimization over the target pose, height and control parameters results in effective strategies for standing, acceleration and deceleration. These strategies improve system performance by orders of magnitude over existing controllers. This paper presents a simple controller for robot motion and an optimization method for choosing its parameters. By using whole-body articulation, we achieve new skills such as standing and unprecedented levels of performance for acceleration and deceleration of the robot base. We describe a new control architecture, present a method for optimization, and illustrate its functionality through two distinct methods of simulation.

Publications

Conference

  • 2012
  • Jiuguang Wang, Eric Whitman, and Mike Stilman Whole-Body Trajectory Optimization for Humanoid Falling American Control Conference. 2012. Best Presentation in Session

    We present an optimization-based control strategy for generating whole-body trajectories for humanoid robots in order to minimize damage in falling. In this work, the falling problem is formulated using optimal control where we seek to minimize the impulse on impact with the ground, subject to the full-body dynamics and constraints of the robot in joint space. We extend previous work in this domain by numerically solving the resulting optimal control problem, generating open-loop trajectories by solving an equivalent nonlinear programming (NLP) problem. These results are illustrated in simulation using the models of dynamically balancing humanoid robots in both wheeled and legged forms. Through the comparison of falling trajectories for the two systems, we demonstrate the advantages of the proposed strategy over previous work in this domain for the effective reduction of the impulse at impact.

    @inproceedings{wang2012wholebody,
      title = {Whole-Body Trajectory Optimization for Humanoid Falling},
      pages = {4837--4842},
      month = {June},
      booktitle = {American Control Conference},
      author = {Jiuguang Wang and Whitman, Eric and Mike Stilman},
      year = {2012}
    }
    
  • 2010
  • Mike Stilman, Jon Olson, and William Gloss Golem Krang: Dynamically Stable Humanoid Robot for Mobile Manipulation IEEE International Conference on Robotics and Automation. 2010.

    What would humans be like if nature had invented the wheel? Golem Krang is a novel humanoid torso designed at Georgia Tech. The robot dynamically transforms from a .5 m static to a 1.5 m dynamic configuration. Our robot development has led to two advances in the design of platforms for mobility and manipulation: (1) A 2-DOF robot base that autonomously stands from horizontal rest; (2) A 4-DOF humanoid torso that adds a waist roll joint to replicate human torso folding and a yaw joint for spine rotation. The mobile torso also achieves autonomous standing in a constrained space while lifting a 40 kg payload. Golem validates our assertions by consistently achieving static-dynamic transformations. This paper describes the design of our mobile torso. It considers a number of factors including its suitability for human environments, mechanical simplicity and the ability to store potential and kinetic energy for handling heavy human and even super-human tasks

    @inproceedings{stilman2010golem,
      title = {Golem Krang: Dynamically Stable Humanoid Robot for Mobile Manipulation},
      pages = {3304--3309},
      month = {May},
      booktitle = {IEEE International Conference on Robotics and Automation},
      author = {Mike Stilman and Olson, Jon and Gloss, William},
      year = {2010}
    }
    
  • Kasemsit Teeyapan, Jiuguang Wang, Tobias Kunz, and Mike Stilman Robot Limbo: Optimized Planning and Control for Dynamically Stable Robots Under Vertical Obstacles IEEE International Conference on Robotics and Automation. 2010.

    We present successful control strategies for dynamically stable robots that avoid low ceilings and other vertical obstacles in a manner similar to limbo dances. Given the parameters of the mission, including the goal and obstacle dimensions, our method uses a sequential composition of IOlinearized controllers and applies stochastic optimization to automatically compute the best controller gains and references, as well as the times for switching between the different controllers. We demonstrate this system through numerical simulations, validation in a physics-based simulation environment, as well as on a novel two-wheeled platform. The results show that the generated control strategies are successful in mission planning for this challenging problem domain and offer significant advantages over hand-tuned alternative

    @inproceedings{teeyapan2010limbo,
      title = {Robot Limbo: Optimized Planning and Control for Dynamically Stable Robots Under Vertical Obstacles},
      pages = {4519--4524},
      month = {May},
      booktitle = {IEEE International Conference on Robotics and Automation},
      author = {Teeyapan, Kasemsit and Jiuguang Wang and Tobias Kunz and Mike Stilman},
      year = {2010}
    }
    
  • 2009
  • Mike Stilman, Jiuguang Wang, Kasemsit Teeyapan, and Ray Marceau Optimized Control Strategies for Wheeled Humanoids and Mobile Manipulators IEEE/RAS International Conference on Humanoid Robotics. 2009. Best Paper Finalist

    Optimizing the control of articulated mobile robots leads to emergent behaviors that improve the effectiveness, efficiency and stability of wheeled humanoids and dynamically stable mobile manipulators. Our simulated results show that optimization over the target pose, height and control parameters results in effective strategies for standing, acceleration and deceleration. These strategies improve system performance by orders of magnitude over existing controllers. This paper presents a simple controller for robot motion and an optimization method for choosing its parameters. By using whole-body articulation, we achieve new skills such as standing and unprecedented levels of performance for acceleration and deceleration of the robot base. We describe a new control architecture, present a method for optimization, and illustrate its functionality through two distinct methods of simulation

    @inproceedings{stilman2009optimized,
      title = {Optimized Control Strategies for Wheeled Humanoids and Mobile Manipulators},
      pages = {568--573},
      month = {December},
      booktitle = {IEEE/RAS International Conference on Humanoid Robotics},
      author = {Mike Stilman and Jiuguang Wang and Teeyapan, Kasemsit and Marceau, Ray},
      year = {2009}
    }
    
  • 2007
  • Satoshi Kagami, Koichi Nishiwaki, James Kuffner, Simon Thompson, Joel Chestnutt, Mike Stilman, and Philipp Michel Humanoid HRP2-DHRC Autonomous and Interactive Behavior Robotics Research: Results of the 12th International Symposium ISRR. Ch. 11. Ed. Thrun, S., Brooks, R.A., and Durrant-Whyte, H.F.. Springer Verlag. 2007.

    Recently, research on humanoid-type robots has become increasingly active, and a broad array of fundamental issues are under investigation. However, in order to achieve a humanoid robot which can operate in human environ- ments, not only the fundamental components themselves, but also the suc- cessful integration of these components will be required. At present, almost all humanoid robots that have been developed have been designed for bipedal locomotion experiments. In order to satisfy the functional demands of loco- motion as well as high-level behaviors, humanoid robots require good me- chanical design, hardware, and software which can support the integration of tactile sensing, visual perception, and motor control. Autonomous behaviors are currently still very primitive for humanoid-type robots. It is difficult to conduct research on high-level autonomy and intelligence in humanoids due to the development and maintenance costs of the hardware. We believe low- level autonomous functions will be required in order to conduct research on higher-level autonomous behaviors for humanoids.

    @inproceedings{kagami2007humanoid,
      title = {Humanoid HRP2-DHRC Autonomous and Interactive Behavior},
      pages = {103--117},
      publisher = {Springer Verlag},
      chapter = {11},
      editor = {Thrun, S. and Brooks, R.A. and Durrant-Whyte, H.F.},
      booktitle = {Robotics Research: Results of the 12th International Symposium ISRR},
      author = {Satoshi Kagami and Nishiwaki, Koichi and James Kuffner and Thompson, Simon and Chestnutt, Joel and Mike Stilman and Michel, Philipp},
      year = {2007}
    }
    

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