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16
Momentum control for balance
- ACM TRANS. ON GRAPHICS
, 2009
"... We demonstrate a real-time simulation system capable of automatically balancing a standing character, while at the same time tracking a reference motion and responding to external perturbations. The system is general to non-human morphologies and results in natural balancing motions employing the en ..."
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Cited by 53 (3 self)
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We demonstrate a real-time simulation system capable of automatically balancing a standing character, while at the same time tracking a reference motion and responding to external perturbations. The system is general to non-human morphologies and results in natural balancing motions employing the entire body (for example, wind-milling). Our novel balance routine seeks to control the linear and angular momenta of the character. We demonstrate how momentum is related to the center of mass and center of pressure of the character and derive control rules to change these centers for balance. The desired momentum changes are reconciled with the objective of tracking the reference motion through an optimization routine which produces target joint accelerations. A hybrid inverse/forward dynamics algorithm determines joint torques based on these joint accelerations and the ground reaction forces. Finally, the joint torques are applied to the free-standing character simulation. We demonstrate results for following both motion capture and keyframe data as well as both human and non-human morphologies in presence of a variety of conditions and disturbances.
Accelerometer-based user interfaces for the control of a physically simulated character
- ACM Trans. on Graphics (SIGGRAPH Asia
, 2008
"... In late 2006, Nintendo released a new game controller, the Wiimote, which included a three-axis accelerometer. Since then, a large variety of novel applications for these controllers have been developed by both independent and commercial developers. We add to this growing library with three performa ..."
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Cited by 34 (0 self)
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In late 2006, Nintendo released a new game controller, the Wiimote, which included a three-axis accelerometer. Since then, a large variety of novel applications for these controllers have been developed by both independent and commercial developers. We add to this growing library with three performance interfaces that allow the user to control the motion of a dynamically simulated, animated character through the motion of his or her arms, wrists, or legs. For comparison, we also implement a traditional joystick/button interface. We assess these interfaces by having users test them on a set of tracks containing turns and pits. Two of the interfaces (legs and wrists) were judged to be more immersive and were better liked than the joystick/button interface by our subjects. All three of the Wiimote interfaces provided better control than the joystick interface based on an analysis of the failures seen during the user study.
Terrain-Adaptive Bipedal Locomotion Control Jia-chi
"... Figure 1: A biped (left) performs a 180 ◦ turn and then walks backwards on uneven terrain and (right) climbs up stairs. We describe a framework for the automatic synthesis of biped locomotion controllers that adapt to uneven terrain at run-time. The framework consists of two components: a per-footst ..."
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Cited by 26 (0 self)
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Figure 1: A biped (left) performs a 180 ◦ turn and then walks backwards on uneven terrain and (right) climbs up stairs. We describe a framework for the automatic synthesis of biped locomotion controllers that adapt to uneven terrain at run-time. The framework consists of two components: a per-footstep end-effector path planner and a per-timestep generalized-force solver. At the start of each footstep, the planner performs short-term planning in the space of end-effector trajectories. These trajectories adapt to the interactive task goals and the features of the surrounding uneven terrain at run-time. We solve for the parameters of the planner for different tasks in offline optimizations. Using the per-footstep plan, the generalized-force solver takes ground contacts into consideration and solves a quadratic program at each simulation timestep to obtain joint torques that drive the biped. We demonstrate the capabilities of the controllers in complex navigation tasks where they perform gradual or sharp turns and transition between moving forwards, backwards, and sideways on uneven terrain (including hurdles and stairs) according to the interactive task goals. We also show that the resulting controllers are capable of handling morphology changes to the character.
Sampling-based Contact-rich Motion Control
"... (a) A forward roll transformed to a dive roll. (b) A cartwheel retargeted to an Asimo-like robot. (c) A walk transformed onto a balance beam. Figure 1: Physically based motion transformation and retargeting. Human motions are the product of internal and external forces, but these forces are very dif ..."
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Cited by 23 (7 self)
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(a) A forward roll transformed to a dive roll. (b) A cartwheel retargeted to an Asimo-like robot. (c) A walk transformed onto a balance beam. Figure 1: Physically based motion transformation and retargeting. Human motions are the product of internal and external forces, but these forces are very difficult to measure in a general setting. Given a motion capture trajectory, we propose a method to reconstruct its open-loop control and the implicit contact forces. The method employs a strategy based on randomized sampling of the control within user-specified bounds, coupled with forward dynamics simulation. Sampling-based techniques are well suited to this task because of their lack of dependence on derivatives, which are difficult to estimate in contact-rich scenarios. They are also easy to parallelize, which we exploit in our implementation on a compute cluster. We demonstrate reconstruction of a diverse set of captured motions, including walking, running, and contact rich tasks such as rolls and kip-up jumps. We further show how the method can be applied to physically based motion transformation and retargeting, physically plausible motion variations, and referencetrajectory-free idling motions. Alongside the successes, we point out a number of limitations and directions for future work. 1
Synthesis of constrained walking skills
- ACM Transactions on Graphics
, 2008
"... Figure 1: Constrained walking skills. (a) Offline synthesis is used to generate physically-simulated motions for example problems. The example motions are used to develop a dynamics model that can make accurate step-to-step predictions. (b) This model can then be used by an online planner to navigat ..."
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Cited by 13 (2 self)
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Figure 1: Constrained walking skills. (a) Offline synthesis is used to generate physically-simulated motions for example problems. The example motions are used to develop a dynamics model that can make accurate step-to-step predictions. (b) This model can then be used by an online planner to navigate across constrained terrain. (c) A 3D physics-based character simulation plans steps to avoid stepping in crevasses. (d) A challenging terrain being navigated by the 3D model. Simulated characters in simulated worlds require simulated skills. We develop control strategies that enable physically-simulated characters to dynamically navigate environments with significant stepping constraints, such as sequences of gaps. We present a synthesis-analysis-synthesis framework for this type of problem. First, an offline optimization method is applied in order to compute example control solutions for randomly-generated example problems from the given task domain. Second, the example motions and their underlying control patterns are analyzed to build a lowdimensional step-to-step model of the dynamics. Third, this model is exploited by a planner to solve new instances of the task at interactive rates. We demonstrate real-time navigation across constrained terrain for physics-based simulations of 2D and 3D characters. Because the framework sythesizes its own example data, it can be applied to bipedal characters for which no motion data is available. 1
Composite control of physically simulated characters
- ACM Trans. on Graphics
, 2011
"... A physics-based control system that tracks a single motion trajectory pro-duces high quality animations, but it does not recover from large distur-bances that require deviating from this tracked trajectory. In order to en-hance the responsiveness of physically simulated characters, we introduce algo ..."
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Cited by 9 (0 self)
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A physics-based control system that tracks a single motion trajectory pro-duces high quality animations, but it does not recover from large distur-bances that require deviating from this tracked trajectory. In order to en-hance the responsiveness of physically simulated characters, we introduce algorithms that construct composite controllers that track multiple trajec-tories in parallel instead of sequentially switching from one control to the other. The composite controllers can blend or transition between different path controllers at arbitrary times according to the current system state. As a result, a composite control system generates both high quality animations and natural responses to certain disturbances. We demonstrate its potential for improving robustness in performing several locomotion tasks. Then we consolidate these controllers into graphs that allow us to direct the character in real time.
Terrain Runner: Control, Parameterization, Composition, and Planning for Highly Dynamic Motions
"... Figure 1: An animated character runs, vaults, jumps, and drop-rolls across a parkour terrain during a real-time physics-based simulation. Given a single motion capture clip of each of these four skills as input, our method uses an offline process to develop robust control policies for parameterized ..."
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Cited by 8 (5 self)
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Figure 1: An animated character runs, vaults, jumps, and drop-rolls across a parkour terrain during a real-time physics-based simulation. Given a single motion capture clip of each of these four skills as input, our method uses an offline process to develop robust control policies for parameterized versions of these skills, as well as robust transition motions. In this paper we learn the skills required by real-time physics-based avatars to perform parkour-style fast terrain crossing using a mix of running, jumping, speed-vaulting, and drop-rolling. We begin with a single motion capture example of each skill and then learn reduced-order linear feedback control laws that provide robust execution of the motions during forward dynamic simulation. We then parameterize each skill with respect to the environment, such as the height of obstacles, or with respect to the task parameters, such as running speed and direction. We employ a continuation process to achieve the required parameterization of the motions and their affine feedback laws. The continuation method uses a predictor-corrector method based on radial basis functions. Lastly, we build control laws specific to the sequential composition of different skills, so that the simulated character can robustly transition to obstacle clearing maneuvers from running whenever obstacles are encountered. The learned transition skills work in tandem with a simple online step-based planning algorithm, and together they robustly guide the character to achieve a state that is well-suited for the chosen obstacle-clearing motion.
Learning Bicycle Stunts
"... We present a general approach for simulating and controlling a hu-man character that is riding a bicycle. The two main components of our system are offline learning and online simulation. We sim-ulate the bicycle and the rider as an articulated rigid body system. The rider is controlled by a policy ..."
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Cited by 3 (0 self)
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We present a general approach for simulating and controlling a hu-man character that is riding a bicycle. The two main components of our system are offline learning and online simulation. We sim-ulate the bicycle and the rider as an articulated rigid body system. The rider is controlled by a policy that is optimized through of-fline learning. We apply policy search to learn the optimal policies, which are parameterized with splines or neural networks for dif-ferent bicycle maneuvers. We use Neuroevolution of Augmenting Topology (NEAT) to optimize both the parametrization and the pa-rameters of our policies. The learned controllers are robust enough to withstand large perturbations and allow interactive user control. The rider not only learns to steer and to balance in normal riding sit-uations, but also learns to perform a wide variety of stunts, includ-ing wheelie, endo, bunny hop, front wheel pivot and back hop.
Modifiable Walking Pattern Generation Handling Infeasible Navigational Commands for Humanoid Robots
"... Abstract – In order to accomplish complex navigational commands, humanoid robot should be able to modify its walking period, step length and direction independently. In this paper, a novel walking pattern generation algorithm is proposed to satisfy these requirements. Modification of the walking pat ..."
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Abstract – In order to accomplish complex navigational commands, humanoid robot should be able to modify its walking period, step length and direction independently. In this paper, a novel walking pattern generation algorithm is proposed to satisfy these requirements. Modification of the walking pattern can be considered as a transition between two periodic walking patterns, which follows each navigational command. By assuming the robot as a linear inverted pendulum, the equations of motion between ZMP(Zero Moment Point) and CM(Center of Mass) state is easily derived and analyzed. After navigational command is translated into the desired CM state, corresponding CM motion is generated to achieve the desired state by using simple ZMP functions. Moreover, when the command is not feasible, feasible command is alternated by using binary search algorithm. Subsequently, corresponding CM motion is generated. The effectiveness of the proposed algorithm is verified by computer simulation.
Physically-based Character Control in Low Dimensional Space
"... Abstract. In this paper, we propose a new method to compose physicallybased character controllers in low dimensional latent space. Source controllers are created by gradually updating the task parameter such as the external force applied to the body. During the optimization, instead of only saving ..."
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Abstract. In this paper, we propose a new method to compose physicallybased character controllers in low dimensional latent space. Source controllers are created by gradually updating the task parameter such as the external force applied to the body. During the optimization, instead of only saving the optimal controllers, we also keep a large number of nonoptimal controllers. These controllers provide knowledge about the stable area in the controller space, and are then used as samples to construct a low dimensional manifold that represents stable controllers. During runtime, we interpolate controllers in the low dimensional space and create stable controllers to cope with the irregular external forces. Our method is best to be applied for real-time applications such as computer games.
