One of the major challenges in optical burst switching networks is the quality of service provision. Some proposals have been made and several limitations have been observed. In this paper, we propose two efficient techniques that enhance the quality of service provided in such networks. The first one deals with optical burst loss during contention resolution process. The second one provides a differentiated service technique using prioritized contention resolution policies in the network core. The two proposed techniques are investigated through extensive simulations. The simulation results show that these techniques lead an effective reduction of the burst average loss rate compared to existing techniques. They also show that a significant differentiation with regard to burst loss can be achieved when burst priorities are considered.

We present a two-level algorithm that incorporates appropriate physical models of the robot, the terrain and their interaction to cope with kinodynamic aspects in all-terrain vehicle motion planning. The high planning level expands a tree of sub-goals in a low dimensional subset of the robot C-space considering a simplified 2D instance of the locomotion task. The second planning level considers locally the full set of task constraints and makes use of a state space formulation to find feasible trajectories and actuator controls moving the robot between adjacent sub-goals. We demonstrate our approach in the case of a six-wheeled articulated vehicle.

Addresses modeling and global motion planning issues for an autonomous wheeled mobile robot moving on an uneven three-dimensional terrain. We focus particularly on the issue of dealing with dynamic and wheel/ground interaction constraints. A key feature of our approach is that it incorporates appropriate physical models to cope with the task dynamics in the motion planning paradigm. The planner is based on a two-level scheme. The high level considers a simplified two-dimensional instance of the motion task and searches a subset of the configuration space of the robot in order to generate nominal subgoals through which the robot is steered. The local level solves for continuous feasible trajectories and actuator controls to move the robot between neighboring subgoals in the presence of the entire task constraints. To the best of our knowledge, this is the first implemented planner that solves for feasible trajectories to be performed by a wheeled vehicle on quite complex terrains. Simulation results are presented for the case of a six-wheeled articulated robot.

We address the global motion planning aspects of dexterous manipulation by a multifingered robotic hand. The specific task we address is: starting from a given initial grasp of a three-dimensional (3-D) object O, find feasible quasistatic trajectories (rolling/sliding motions and forces) for the fingertips to move O to a desired final configuration. We call this the reconfiguration problem. Our planner is based on a two-level algorithm combining a graph search on the configuration space of the object and a local planner that solves for instantaneous quasistatic motions of the entire manipulation system. The planner is used for simulating several complex reconfiguration tasks for smooth objects demonstrating the promise of our approach.

This paper addresses the problem of planning collision-free motions for a fleet of mobile robots moving in a cluttered and changing workspace. We focus on the problem of planning handling operations in an industrial plant: find a collision-free trajectory for a set of mobile robots for handling a group of movable objects in a cluttered industrial plant. The motion planner we describe copes with constraints due to changing of the workspace by decomposing the planning problem into 2 stages: (1) building a single roadmap by pre-processing the C-space of the moving systems, and (2) planning coordinated collision-free paths for these systems including manipulation of the roadmap to guarantee the incorporation of the workspace changing. The planner has been implemented and demonstrated on 2D models of industrial plants.

This paper describes a global motion planner for dextrous manipulation of 3D objects by a multifingered robotic hand. We focus on the reconfiguration problem: find a feasible quasi-static trajectory (motions and contact forces) that moves a hand-object system from an initial grasp to a final desired configuration of the object. The planner is designed as a two-level process: a global level that expands a tree of sub-goals in the configuration space of the object, and a local level that searches for feasible quasi-static trajectories of the entire manipulation system between adjacent sub-goals. A key feature of the planner is that it exploits the redundancy of the system by using, in a complementary way, different canonical manipulation modes and tackles the high dimensionality of the solution space (configuration and control spaces) by making use, instantaneously, of a random search over it. The planner is applied in simulation for achieving several nontrivial reconfiguration tasks for (piecewise-) smooth convex objects demonstrating the promise of our approach.

We address the global motion planning aspects of dextrous manipulation by a multifingered robotic hand. The specific task we address is: starting from a given initial grasp of a 3D object O, find feasible quasi-static trajectories (rolling/sliding motions and forces) for the fingertips to move O to a desired final configuration. We call this the re-configuration problem. Our planner is based on a two-level algorithm combining a graph search on the configuration space of the object and a local planner that solves for instantaneous quasi-static motions of the entire manipulation system. The planner is used for several complex re-configuration tasks-for polyhedral and smooth objects. These experiments show the practicality of our approach.

This paper addresses the motion planning problem for dextrous manipulation by an artificial multifingered hand. We focus on the task of re-orienting polyhedral objects and present a practical motion planner for achieving quasistatic manipulations by a four-fingered hand. The planner makes use of a simple manipulation strategy in which a single finger is moved and the other three are fixed. We describe how this scenario is exploited for reducing the space of trajectory solutions and used within a two-level incremental process to search for global re-orientation motions. The planner has been implemented and used for achieving several complex re-orientation tasks with frictional and frictionless contacts that show the practicality of our approach.

We describe in this paper a new motion planning approach for a nonholonomic mobile robot moving on an uneven terrain and subject to strong physical interaction constraints. The novelty of this method is that it deals with the dynamics of the robot and its physical interactions with the terrain at the planning time, together with the kinematic and the geometric constraints of the task. The planner basically combines a geometry-based reasoning strategy operating on a subset of the configuration space of the robot, and a local continuous motion generation technique based on the use of a physical model of the task. We will describe each level and its corresponding models, and present how they are integrated in order to find safe and executable motions for a rover.

This paper addresses motion planning for a mobile robot moving on a hilly three dimensional terrain and subjected to strong physical interaction constraints. The main contribution of this paper is a planning method which takes into account the dynamics of the robot, the robot/terrain interactions, the kinematic constraints of the robot, and classical constraints. The basic idea of our method is to integrate geometric and physical models of the robot and of the terrain in a two-stage trajectory planning process. Consisting in combining a "discrete search strategy" and a "continuous motion generation method". It will be shown how each planning step operates and how they interact in order to generate a safe and executable motion for the all-terrain vehicle.>

This paper deals with motion, planning for a mobile robot moving on a hilly three dimensional terrain and subjected to strong physical interaction. Constraints. The main contribution of this paper is a planning method which takes into account the dynamics of the robot, the robot/terrain interactions, the kinematic constraints of the robot, and classical constraints. The basic idea of the authors' method is to integrate geometric and physical models of the robot and of the terrain in a two-stage trajectory planning process consisting of combining a "discrete search strategy" and a "continuous motion generation method". It is shown how each planning step operates and how they interact in order to generate a "safe" and executable motion for the all-terrain vehicle.>