Computing shortest paths is one of the most researched topics in algorithm engineering. Currently available algorithms compute shortest paths in mere fractions of a second on continental sized road networks. In the presence of unreliability, however, current algorithms fail to achieve results as impressive as for the static setting. In contrast to speed-up techniques for static route planning, ...

The paper introduces the Switching Four-bar Mechanism (sfm), a new low-dimensional kinematic abstraction forminiature legged robots, aimed at quasi-static motion planning in the horizontal plane. The model comprises a rigid torso and four rigid legs which engage in an alternating tetrapod gait. As the gait is executed, the torso and the legs form two switching four-bar linkages, parameterized b...

A systematic approach to the static analysis of deformation of linear objects such as cords and ropes is presented. There exists many manipulative operations that deal with deformable objects in environments that robots are expected to take active parts, while rigid object manipulation has been a main interest in most of the task planning researches. Manipulative operations that deal with defor...

DISCOPLAN is an efficient system for discovering state invariants in planning domains with conditional effects. Among the types of invariants found are implicative constraints relating a fluent predication to a fluent or static predication (with allowance for static supplementary conditions), single-valuedness constraints, exclusiveness constraints, and several others. The algorithms used are p...

We have designed a two-stage scheme to consider the trajectory planning problem of two mobile manipulators for cooperative transportation of a rigid body in the presence of static obstacles. In the first stage, with regard to the static obstacles, we develop a method that searches the workspace for the shortest possible path between the start and goal configurations, by constructing a graph on ...

To guarantee safe motion planning, the underlying path planning algorithm must consider uncertainties and uncertain state information related to static, dynamic obstacles. This paper proposes novel hybrid A* (HA*) algorithms that uncertainty in of a mobile robot, position static obstacles, velocity Variants HA* are proposed wherein soft constraint is used cost function instead chance constraint...

Providing a higher level of decision autonomy is a true challenge in development of today AUVs and promotes a single vehicle to accomplish multiple tasks in a single mission as well as accompanying prompt changes of a turbulent and highly uncertain environment, which has not been completely attained yet. The proceeding approach builds on recent researches toward constructing a comprehensive str...

One of the most important problems studied in wireless sensor network applications is the collaborative processing among sensor nodes in order to compensate for each other’s sensing and computing capabilities and to tolerate faults. The client/server based paradigm and the mobile agent based paradigm are two popular computing models used in collaborative processing. One of the most challenging ...

Two main challenges of robot action planning in real domains are uncertain action effects and dynamic environments. In this paper, an instance-based action model is learned empirically by robots trying actions in the environment. Modeling the action planning problem as a Markov decision process, the action model is used to build the transition function. In static environments, standard value it...

Automated planning is a classical area of artificial intelligence research that is concerned with the problem of planning a course of action for an agent (or set of agents) acting in a complex environment. In the frequently studied case of classical planning, e. g. in the propositional STRIPS formalism [1], the problem is that of finding a sequence of actions that achieves the goal of a single ...