Over the past few years, simulating crowds in virtual environments has become an important tool to give life to virtual scenes; be it movies, games, training applications, etc. An important part of crowd simulation is the way that people move from one place to another. This paper concentrates on improving the crowd patches approach proposed by Yersin et al. [Yersin et al. 2009] that aims on efficiently animating ambient crowds in a scene. This method is based on the construction of animation blocks (called patches) concatenated together under some constraints to create larger and richer animations with limited run-time cost. Specifically, an optimization based approach to generate smooth collision free trajectories for crowd patches is proposed. The contributions of this work to the crowd patches framework are threefold; firstly a method to match the end points of trajectories based on the Gale-Shapley algorithm [Gale and Shapley 1962] is proposed that takes into account preferred velocities and space coverage, secondly an improved algorithm for collision avoidance is proposed that gives natural appearance to trajectories and finally a cubic spline approach is used to smooth out generated trajectories. We demonstrate several examples of patches and how they were improved by the proposed method, some limitations and directions for future improvements.

Abstract This paper deals with whole‐body motion planning and dynamic control for humanoid from two aspects: locomotion including manipulation and reaching. In the first part, we address a problem of simultaneous locomotion and manipulation planning that combines a geometric and kinematic motion planner with a dynamic humanoid motion generator. The second part deals with whole‐body reaching tasks by using a generalized inverse kinematics (IK) method to fully exploit the high redundancy of the humanoid robot. Through experiments using humanoid platform HRP‐2 No. 14 installed at LAAS‐CNRS, we first verify the validity of each method. An integrated experiment is then presented that unifies the both results via visual perception to execute an object‐fetching task. Copyright © 2009 John Wiley & Sons, Ltd.

We propose a general and practical planning framework for generating 3-D collision-free motions that take complex robot dynamics into account. The framework consists of two stages that are applied iteratively. In the first stage, a collision-free path is obtained through efficient geometric and kinematic sampling-based motion planning. In the second stage, the path is transformed into dynamically executable robot trajectories by dedicated dynamic motion generators. In the proposed iterative method, those dynamic trajectories are sent back again to the first stage to check for collisions. Depending on the application, temporal or spatial reshaping methods are used to treat detected collisions. Temporal reshaping adjusts the velocity, whereas spatial reshaping deforms the path itself. We demonstrate the effectiveness of the proposed method through examples of a space manipulator with highly nonlinear dynamics and a humanoid robot executing dynamic manipulation and locomotion at the same time.

This video demonstrates our current investigation in developing autonomous behaviors for humanoid robots. Our main goal is to develop functionalities as much generic as possible in order to realize useful behaviors. More particularly this video demonstrates our current status on extending a popular zero momentum problem (ZMP) preview control based pattern generator, and building some links between walking with vision.

In this paper we address smooth and collision-free whole-body motion planning for humanoid robots. A two-stage iterative planning framework is introduced where geometric motion planner and dynamic pattern generator interacts by exchanging the trajectory, to obtain 3D whole-body dynamic motions simultaneous tasks including locomotion, in complex environments. We propose a practical method for smooth motion reshaping to avoid collisions in generated dynamic motion. Based on motion editing techniques in computer graphics animation, smooth collision-avoiding motion is generated through trajectory deformation. The validity of the proposed reshaping method is verified by computer simulations and experiments using humanoid platform HRP-2

This paper presents an approach to automatically compute animations for virtual (human-like and robot) characters cooperating to move bulky objects in cluttered environments. The main challenge is to deal with 3D collision avoidance while preserving the believability of the agent's behaviors. To accomplish the coordinated task, a geometric and kinematic decoupling of the system is proposed. This decomposition enables us to plan a collision-free path for a reduced system, then to animate locomotion and grasping behaviors independently, and finally to automatically tune the animation to avoid residual collisions. These three steps are applied consecutively to synthesize an animation. The different techniques used, such as probabilistic path planning, locomotion controllers, inverse kinematics and path planning for closed kinematic chains are explained, and the way to integrate them into a single scheme is described.

This paper deals with motion planning algorithms for the large space robot manipulators with complicated dynamic behavior. We propose two "two-stage" iterative algorithms, which provide collision-free robot motion taking into account robot's dynamics. The approach is based on new efficient methods for robot manipulator dynamics simulation and probabilistic methods for motion planning in highly cluttered environments. The algorithms are applicable for the robot manipulators of general class with arbitrary kinematics and dynamics parameters. We have demonstrated the approach for a particular task of servicing the satellite by a large space manipulator. This task is one of the most challenging since large space manipulators have extremely complicated dynamic behavior caused by elasticity of their structure, huge payloads they work with and zero-gravity conditions. Experiments involving a 15.5 meters long manipulator carrying a satellite inside a space shuttle with clearance less than 3 cm are presented. Several movies demonstrate the results.

This paper presents a motion planner for a digital mannequin carrying objects in cluttered environments. The goal is to account for 3-dimensional obstacle avoidance, eye-convincing locomotion as well as manipulation constraints within an integrated motion planning approach. This approach combines probabilistic path planning methods, a motion capture based walking controller and inverse kinematics techniques.

In this paper a complete strategy for scene modelling from sensory data acquired in a natural environment is defined. This strategy is applied to outdoor mobile robotics, from environment recognition to landmark extraction. In this work, an environment is understood as a specific kind of landscape, for instance prairie, forest, desert, etc. A landmark is defined as a conspicuous object in the environment. In the context of outdoor mobile robotics a landmark has to be useful to perform localization and navigation tasks.

This article describes the integration in a complete navigation system of an environment modeling method based on a Generalized Voronoi Graph (GVG), relying on laser data, on the one hand, and of a localization method based on monocular vision landmark learning and recognition framework, on the other hand. Such a system is intended to work in structured environments. It is shown that the two corresponding modules - laser GVG construction and visual landmarks learning and recognition - can cooperate to complete each other, as image processing can be enhanced by some structural knowledge about the scene, whereas the GVG is annotated, even as far as its edges are concerned, by qualitative visual information.

The goal of this work is to develop techniques that allow one or more robotic observers to operate with full autonomy while accomplishing the task of model building. The planning algorithm operates using certain simple but flexible models of the observer sensor and actuator abilities. We provide techniques that allow us to implement these sensor models on top of the capabilities of the actual (and off-the-shelf) sensors we have. It is worth keeping the following points in mind regarding our goals: 1) even with completely idealized sensing and mobility capabilities, the algorithmic task of model building is quite challenging; 2) computational techniques can be used to approximate and implement these idealized sensors on top of actual sensors; and 3) the quality and success of the generated plans depend significantly on the observer capabilities. The study of this dependency terms of high-level parameters describing the sensors is part of this work.