Planning biped locomotion using motion capture data and probabilistic roadmaps

Choi, Min; Lee, Jehee; Shin, Sung Yong

doi:10.1145/636886.636889

Cited by 155 publications

(109 citation statements)

References 59 publications

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“…The former simplifies the process of creating final hand motion and the latter greatly reduces the number of required samples. A few applications in computer animation adopt randomized path planning algorithms from robotics literature [Choi et al 2003;Yamane et al 2004]. Our problem is different in that the dynamic constraint in contacts defines a narrow and nonsmooth feasible region.…”

Section: Related Workmentioning

confidence: 99%

Synthesis of detailed hand manipulations using contact sampling

Liu

2012

ACM Trans. Graph.

112

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Capturing human activities that involve both gross full-body motion and detailed hand manipulation of objects is challenging for standard motion capture systems. We introduce a new method for creating natural scenes with such human activities. The input to our method includes motions of the full-body and the objects acquired simultaneously by a standard motion capture system. Our method then automatically synthesizes detailed and physically plausible hand manipulation that can seamlessly integrate with the input motions. Instead of producing one "optimal" solution, our method presents a set of motions that exploit a wide variety of manipulation strategies. We propose a randomized sampling algorithm to search for as many as possible visually diverse solutions within the computational time budget. Our results highlight complex strategies human hands employ effortlessly and unconsciously, such as static, sliding, rolling, as well as finger gaits with discrete relocation of contact points.

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Section: Related Workmentioning

confidence: 99%

Synthesis of detailed hand manipulations using contact sampling

Liu

2012

ACM Trans. Graph.

112

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“…Finally, a walking animation is generated according these variations. Another approach based on PRM is presented in [9]. The roadmap is constructed by randomly sampling foot positions and orientations to form the graph nodes.…”

Section: Motion Planningmentioning

confidence: 99%

“…To solve this problem, the algorithms presented in [9] may be applied. It consists in generating randomly a series of footprints between the start and the end of the run-up motion, and then in adapting an appropriate motion capture clip.…”

Section: Run-up Footprint Computationmentioning

confidence: 99%

“…As opposed to traditional methods that consider the objects (or obstacles) of a scene as static [9,14,32] or as described with pre-defined trajectories [16,23], we aim at handling obstacles that are not known in advance, generated on-thefly during the animation process. Based on a locomotion engine, the character moves freely in a virtual environment.…”

Section: Introductionmentioning

confidence: 99%

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Dynamic obstacle avoidance for real-time character animation

2006

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This paper proposes a novel method to control virtual characters in dynamic environments. A virtual character is animated by a locomotion and jumping engine, enabling production of continuous parameterized motions. At any time during runtime, flat obstacles (e.g. a puddle of water) can be created and placed in front of a character. The method first decides whether the character is able to get around or jump over the obstacle. Then the motion parameters are accordingly modified. The transition from locomotion to jump is performed with an improved motion blending technique. While traditional blending approaches let the user choose the transition time and duration manually, our approach automatically controls transitions between motion patterns whose parameters are not known in advance. In addition, according to the animation context, blending operations are executed during a precise period of time to preserve specific physical properties. This ensures coherent movements over the parameter space of the original input motions. The initial locomotion type and speed are smoothly varied with respect to the required jump type and length. This variation is carefully computed in order to place the take-off foot as close to the created obstacle as possible.

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“…Within these planners, locomotion and manipulation have been treated separately. Two-dimensional locomotion planners have been proposed in [6], [14]. In our work, the 3-dimensionality of the environment is taken into account.…”

Section: Related Work and Contributionmentioning

confidence: 99%

Motion planning for human-robot interaction in manipulation tasks

Esteves

Arechavaleta

Laumond

IEEE International Conference Mechatronics and Automation, 2005

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Abstract-This paper presents a motion planner to automatically compute animations for virtual (human, humanoid or robot) mannequins cooperating to move bulky objects in cluttered environments. The main challenge is to deal with 3D collision avoidance while preserving the believability of the agents behaviors. To accomplish the coordinated task, a geometric and kinematic decoupling of the system is proposed. This decomposition enables us to plan a collisionfree path for a reduced system, then to animate locomotion and grasping behaviors in parallel, and finally to clean up the animation from residual collisions. These three steps are automatically applied making use of different techniques such as probabilistic path planning, locomotion controllers, inverse kinematics and path planning for closed-kinematic mechanisms.

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Planning biped locomotion using motion capture data and probabilistic roadmaps

Cited by 155 publications

References 59 publications

Synthesis of detailed hand manipulations using contact sampling

Synthesis of detailed hand manipulations using contact sampling

Dynamic obstacle avoidance for real-time character animation

Motion planning for human-robot interaction in manipulation tasks

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