We propose a new approach for the reliable 6dimensional quasi-static manipulation of an aerial towed-cable system. The novelty of this approach lies in the combination of results deriving from the static analysis of cable-driven manipulators with the application of a cost-based motion-planning algorithm to solve manipulation queries. Using this approach, we can ensure that the produced paths ar...

Dynamic environments, in which robots and for example humans share a common workspace impose a variety of requirements on path planning algorithms, including real-time capabilities and collision tests based on sensor input. We propose a randomized-roadmap-based path planning algorithm that limits the number of collision tests and distance calculations to a volume achievable in realtime, while s...

Domain-independent planning systems require that domain constraints and invariants are specified as part of the input domain model. In AI Planning, the generated plan is correct provided the constraints of the world in which the agent is operating are satisfied. Specifying operator descriptions by hand for planning domain models that also require domain specific constraints is time consuming, e...

as route planning and resource handling. Using static domain analysis techniques, we have been able to identify certain commonly occurring subproblems within planning domains, making it possible to abstract these subproblems from the overall goals of the planner and deploy specialized technology to handle them in a way integrated with the broader planning activities. Using two such subsolvers o...

Opponent behavior in today's computer games is often the result of a static set of Artificial Intelligence (AI) behaviors or a fixed AI script. While this ensures that the behavior is reasonably intelligent, it also results in very predictable behavior. This can have an impact on the replayability of entertainment-based games and the educational value of training-based games. This paper propose...

When navigating in crowds, humans are able to move efficiently between people. They look ahead to know which path would reduce the complexity of their interactions with others. Current navigation systems for virtual agents consider long-term planning to find a path in the static environment and short term reactions to avoid collisions with close obstacles. Recently some mid-term considerations ...

Transmission network expansion planning is a very complex and computationally demanding problem due to the discrete nature of the optimization variables. This complexity has increased even more in a restructured deregulated environment. In this regard, there is a need for development of more rigorous optimization techniques. This paper presents a comparative analysis of three metaheuristic algo...

The mobile agent based paradigm is a promising computing paradigm in wireless sensor networks, which has many unique advantages over the traditional client/server paradigm. However, the question on how to model the mobile agent itinerary in sensor networks, is left unsolved. The design of the mobile agent migration itinerary has a large impact on the performance of collaborative processing, whi...

The Autonomous Underwater Vehicle (AUV) three-dimension path planning in complex turbulent underwater environment is investigated in this research, in which static current map data and uncertain static-moving time variant obstacles are taken into account. Robustness of AUVs path planning to this strong variability is known as a complex NP-hard problem and is considered a critical issue to ensur...

We discuss how a path planning problem for a robotic platform was solved modeling it with the axioms of the action language AL and described in Answer Set Programming, ASP. The environment of the autonomous vehicle is static. A set of dynamic, static and inertial laws are used to describe the vehicle domain. The optimum solution is chosen using two criteria: minimum distance and minimum obstacl...