Airline deregulation is spreading worldwide and has important consequences for the planning, design, and management of airports. One important effect is that the overall traffic at an airport -and by extension its revenues is much more volatile in a liberal environment. This is demonstrated by analysis of the US experience over the last twenty-five years. The increased risk thus associated with...

In many robot motion planning problems such as manipulation planning for a personal robot in a kitchen or an industrial manipulator in a warehouse, all motion planning queries are in an environment that is largely static. Consequently, one should be able to improve the performance of a planning algorithm by training on this static environment ahead of operation time. In this work, we propose a ...

Urban Traffic Control is a key problem for most big cities. An inefficient traffic control system can lead to increased traffic congestions that degrade city quality metrics such as average travel time or city pollution. Most common approaches focus on controlling traffic by appropriately setting traffic lights. Current systems in operation range from static control of traffic light phases to a...

The work presented in this paper aims to model and solve multi-criteria international itinerary planning problems The emerging itinerary planning problems are defined on a multimodal time-dependent transportation network that consists of hierarchically interconnected international, interurban and urban transportation networks. The itinerary planning problems under study fall into two major cate...

Domain independent AI planning systems must be able to efficiently generate solutions if they are to be widely deployed to solve large scale real world problems. This paper suggests a static domain analysis technique that can be used to derive heuristics (called general memos) that can be used by Graphplan, one of the most efficient algorithms for solving the classical AI planning problem, to i...

This paper presents an example of cooperation between AI planning techniques and Constraint Programming or Operations Research. More precisely, it presents a way of boosting forward planning using combinatorial optimization techniques. The idea consists in combining on one hand a dynamic model that represents the Markovian dynamics of the system considered ( i.e. state transitions), and on the ...

A new global path planning approach based on particle swarm optimization (PSO) for a mobile robot in a static environment is presented. Consider path planning as an optimization problem with constraints. The constraints are the path can not pass by the obstacles. The optimization target is the path is shortest. The obstacles in the robot’s environment are described as polygons and the vertexes ...

This paper presents a new motion planning algorithm for wheeled mobile robots in presence of known static obstacles, especially well-suited for high velocity situations. It takes into account several conditions traditionally attached to smooth path planning, i.e. paths with continuous derivative and upper-bounded curvature. It makes use of a global path planner which exploits polynomial G curve...

optimal balancing is a new approach based on optimal control a which modes, controls and the amount of equilibrium scale are calculated simultaneously. this approach has a significant effect on increasing performance of industrial robots which causes maximum decreasing of energy consumption. despite many applications of robotics such as welding and gluing, the path is predefined , but other unk...