Simulating balance recovery responses to trips based on biomechanical principles

Shiratori, Takaaki; Coley, Brooke; Cham, Rakié; Hodgins, Jessica K.

doi:10.1145/1599470.1599475

Cited by 36 publications

(12 citation statements)

References 32 publications

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“…Both responses are well known behaviors in disturbed human swing phases [26]. In contrast to generating these responses with explicitly triggered control [18], [27], they are inherent to the identified leg placement control.…”

Section: Discussionmentioning

confidence: 99%

Robust swing leg placement under large disturbances

Desai

Geyer

2012

2012 IEEE International Conference on Robotics and Biomimetics (ROBIO)

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Swing leg placement is vital to dynamic stability in legged robots and animals. The most common approaches to generating swing leg motions in robotics use either position or impedance tracking of defined joint trajectories. While these approaches suffice in humanoids, they severely limit swing leg placement under large disturbances in prosthetic limbs, for which stabilizing reactions cannot be planned centrally. Rather than careful central planning, animals and humans seem to rely on local feedback control for reliable swing leg placement. Motivated by this observation, we here present an alternative for generating swing leg motions. We develop a local swing leg control that takes advantage of segment interactions to achieve robust leg placement under large disturbances while generating trajectories and joint torque patterns similar to those patterns observed in human walking and running. The results suggest the identified control as a powerful alternative to existing swing leg controls in humanoid and rehabilitation robotics.

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Section: Discussionmentioning

confidence: 99%

Robust swing leg placement under large disturbances

Desai

Geyer

2012

2012 IEEE International Conference on Robotics and Biomimetics (ROBIO)

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“…To capture more dynamic variations of rising motions, especially balancing behaviors from sitting/squatting to standing, it is desirable to simulate the whole motion from lying to stance states. Several recent approaches [18,19,24] can be applied to improve our dynamics filtering. We will explore the above issues about motion planning and dynamics filtering in the future.…”

Section: Discussion and Limitationsmentioning

confidence: 99%

Animating rising up from various lying postures and environments

Lin

Huang

2011

Vis Comput

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Generating rising up motions is an important problem but has less been addressed in computer animation. This problem is challenging as rising motions involve complex motor skills and exhibit wide varieties due to various lying postures and environments. In this paper, we present an approach that utilizes motion planning and dynamics filtering to produce physically plausible rising motions. Our motion planning algorithm connects a given posture to a closest posture in a database of 14 rising motions. Then the dynamics filtering generates a physically plausible motion from a planned motion path. Our experiments show that a variety of motions of rising from various lying postures and different environments with obstacles can be generated easily by our approach.

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“…Some researchers also investigated the simulation of reactive and responsive motions integrated with walking or standing behaviors with or without the help of biomechanic strategies ( [22], [23], [24], [25]). Furthermore, there other studies that control the flight-based rotational behaviors, such as falling and rolling ( [26], [27]).…”

Section: Physics-based Approachesmentioning

confidence: 99%

Skill learning based catching motion control

Cimen

Kavafoglu

et al. 2015

Computer Animation & Virtual

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In real world, it is crucial to learn biomechanical strategies that prepare the body in kinematics and kinetics terms during the interception tasks, such as kicking, throwing and catching. Based on this, we presents a real-time physics-based approach that generate natural and physically plausible motions for a highly complex task-ball catching. We showed that ball catching behavior as many other complex tasks, can be achieved with the proper combination of rather simple motor skills, such as standing, walking, reaching. Since learned biomechanical strategies can increase the conscious in motor control, we concerned several issues that needs to be planned. Among them, we intensively focus on the concept of timing. The character learns some policies to know how and when to react by using reinforcement learning in order to use time accurately. We demonstrate the effectiveness of our method by presenting some of the catching animation results executed in different catching strategies.In each simulation, the balls were projected randomly, but within a interval of limits, in order to obtain different arrival flight time and height conditions.

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Simulating balance recovery responses to trips based on biomechanical principles

Abstract: To realize the full potential of human simulations in interactive environments

Cited by 36 publications

References 32 publications

Robust swing leg placement under large disturbances

Robust swing leg placement under large disturbances

Animating rising up from various lying postures and environments

Skill learning based catching motion control

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