In this paper parameter-free concepts for exact motion planning are investigated. With the proposed RDT approach the collision detection parameters of a Rapidlyexploring Dense Tree (RDT) are automatically adjusted until an exact solution can be found. For efficient planning discrete collision detection routines are used within the RDT planner and by verifying the results with exact collision de...

Navigation in large dynamic spaces has been often adressed using deterministic representations, fast updating and reactive avoidance strategies. However, probabilistic representations are much more informative and their use in mapping and prediction methods improves the quality of obtained results. The paper proposes a new concept to integrate a probabilist collision risk function linking plann...

Modern robot soccer control architectures tend to separate higher level tactics and lower level navigation control. This can lead to tactics which do not fully utilize the robot’s dynamic actuation abilities. It can furthermore create the problem of the navigational code breaking the constraints of the higher level tactical goals when avoiding obstacles. We aim to improve such control architect...

We study the planning problem of selecting services and transfers in a synchromodal network to transport freights with different characteristics, over a multi-period horizon. The evolution of the network over time is determined by the decisions made, the schedule of the services, and the new freights that arrive each period. Although freights become known gradually over time, the planner has pr...

In the stream of research that aims to speed up practical planners, we propose a new approach to task planning based on Probabilistic Roadmap Methods (PRM). Our contribution is twofold. The rst issue concerns an extension of GraphPlan[1] specially designed to deal with \local planning" in large domains. Having a reasonably e cient \local planner", we show how we can build a \global task planner...

This paper presents a real-time path planning algorithm that guarantees probabilistic feasibility for autonomous robots with uncertain dynamics operating amidst one or more dynamic obstacles with uncertain motion patterns. Planning safe trajectories under such conditions requires both accurate prediction and proper integration of future obstacle behavior within the planner. Given that available...

In this paper, we study the completeness of the 0approximation for action theories with incomplete information. We propose a sufficient condition for which an action theory under the 0-approximation semantics is complete with respect to the possible world semantics. We then introduce the notion of decisive sets of fluents, based on which an action theory can be modified into another action theo...

Semester planner plays an essential role in students’ society that might help students have self-discipline and determination to complete their studies. However, during the COVID-19 pandemic, they faced difficulty organizing time management doing a manual schedule. It resulted substantial disruptions learning, internal assessment disturbances, cancellation of public evaluations. Hence, this res...

The problem of on-line planning in partially observable settings involves two problems: keeping track of beliefs about the environment and selecting actions for achieving goals. While the two problems are computationally intractable in the worst case, significant progress has been achieved in recent years through the use of suitable reductions. In particular, the state-of-the-art CLG planner is...