Interactive navigation in complex environments using path planning

The probabilistic roadmap approach is one of the leading motion planning techniques. Over the past decade the technique has been studied by many different researchers. This has led to a large number of variants of the approach, each with its own merits. It is difficult to compare the different techniques because they were tested on different types of scenes, using different underlying libraries, implemented by different people on different machines. In this paper we provide a comparative study of a number of these techniques, all implemented in a single system and run on the same test scenes and on the same computer. In particular we compare collision checking techniques, sampling techniques, and node adding techniques. The results were surprising in the sense that techniques often performed differently than claimed by the designers. The study also showed how difficult it is to evaluate the quality of the techniques. The results should help future users of the probabilistic roadmap planning approach in deciding which technique is suitable for their situation.

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“…This should lead to a much better spread of the samples over the configuration space. A similar approach was employed in [32].…”

Section: Uniform Samplingmentioning

confidence: 99%

Sampling and node adding in probabilistic roadmap planners

Gerærts

Overmars

2006

Robotics and Autonomous Systems

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“…Recently, a few researches have attempted to use the technologies developed in Artificial Intelligence (AI) to design intelligent interface to assist user navigation. For example, using guided navigation, motion planning techniques, and virtual forces are all examples in this direction [12][7] [8]. However, the mechanisms designed in these researches are all applied to the first-person control only.…”

Section: A Intelligent 3d Control Interfacementioning

confidence: 99%

“…However, the mechanisms designed in these researches are all applied to the first-person control only. [12] has applied motion planning techniques to generate avatar gross motions but finer limb movements are not taken into account. [11] uses a two-stage planning strategy to generate global motion and finer upper body motion in two steps but the planning is not incorporated into the real-time loop of user interface control.…”

Section: A Intelligent 3d Control Interfacementioning

confidence: 99%

“…In the literature, several researches have used motion planning techniques to assist user navigation in a virtual environment [12] [7]. The work in [12] proposed to assist user navigation by generating a guided path closely followed by the avatar at run time.…”

Section: Introductionmentioning

confidence: 99%

“…The work in [12] proposed to assist user navigation by generating a guided path closely followed by the avatar at run time. In [7] the proposed system allows a user to control the viewpoint freely until the viewpoint is obstructed by obstacles.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Third-Person Interactive Control of Humanoid with Real-Time Motion Planning Algorithm

Hsu

2006

2006 IEEE/RSJ International Conference on Intelligent Robots and Systems

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-Interactive avatar control means a control mechanism using AI techniques to improve user navigation efficiency as well as visual realism in a 3D virtual environment. This paper reports a novel approach to enhancing intelligent navigation interface with a third-person control mechanism. We use the concept of CT-space roadmap to design a new motion planning algorithm that can generate collisionfree motions for the upper-body of an avatar walking in a cluttered virtual environment. We have designed a mechanism to allow motion generation and execution to occur in parallel such that collision-free motions can be generated in real time. We believe that this type of intelligent interface can enhance the efficiency of avatar navigation as well as improve the realism of the generated avatar motions. The same techniques can also be applied to the motion control of humanoid robots to avoid obstacles in real time.

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Automatic generation of human animation based on motion programming

Zhuang¹,

Xiao

Wu³

et al. 2005

Computer Animation & Virtual

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In motion simulations, video games and animation films, lots of interactions between characters and virtual environments are needed. Even though realistic motion data can be derived from MoCap system, motion editing and synthesis, animators must adapt these motion data to specific virtual environment manually, which is a boring and time‐consuming job. Here we propose a framework to program the movements of characters and generate navigation animations in virtual environment. Given a virtual environment, a visual user interface is provided for animators to interactively generate motion scripts, describing the characters' movements in this scene and finally used to retrieve motion clips from MoCap database and generate navigation animations automatically. This framework also provides flexible mechanism for animators to get varied resulting animations by configurable table of motion bias coefficients and interactive visual user interface. Copyright © 2005 John Wiley & Sons, Ltd.

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Interactive navigation in complex environments using path planning

Cited by 31 publications

References 0 publications

Sampling and node adding in probabilistic roadmap planners

Sampling and node adding in probabilistic roadmap planners

Third-Person Interactive Control of Humanoid with Real-Time Motion Planning Algorithm

Automatic generation of human animation based on motion programming

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