Grid-based methods for finding cost optimal paths are popular because of their flexibility and simple implementation. However, their computational complexity becomes unfeasible for real-time path planning if the resolution of the grid is high. These methods assume complete knowledge about the world, but in dynamic environments where sensing is done on board the robot, less is known about far-aw...

In this paper, we give a double twist to the problem of planning under uncertainty. State-of-the-art planners seek to minimize the localization uncertainty by only considering the geometric structure of the scene. In this paper, we argue that motion planning for vision-controlled robots should be perception aware in that the robot should also favor texture-rich areas to minimize the localizatio...

Deceptive path-planning involves finding a path such that the probability of an observer identifying its final destination—before it has been reached— is minimised. This paper formalises deception as it applies to path-planning and introduces the notion of a last deceptive point (LDP) which, when measured in terms of path completion, can be used to rank paths by their potential to deceive. Buil...

Path planning is dynamic when the path is continually recomputed as more information becomes available. A computational framework for dynamic path planning is proposed which has the ability to provide navigational directions during the computation of the plan. Path planning is performed using a potential eld approach. We use a speciic type of potential function a harmonic function-which has no ...

This paper describes a combined mathematicalgraphical approach for optimum tool path planning in order to improve machining efficiency. A methodology has been used that stabilizes machining operations by adjusting material removal rate in pocket milling operations while keeping cutting forces within limits. This increases the life of cutting tool and reduces the risk of tool breakage, machining...

Unmanned Aerial Vehicles (UAV) become more and more popular today. The chairman of DJI which is one of the most important UAV producers told an online magazine that their turnover increased by a factor of four in the last years [1]. This development validates the increasing popularity of UAVs. But it is still challenging to control them and it is even more challenging to film important surface ...

Probabilistic Roadmaps (PRM) [1] is an algorithm for finding a collision-free path in a known environment. It works by sampling possible configurations qi of the robot in the configuration space, C, and making connections between ”near” configurations with a local planner (i.e. straight lines of bounded length). A recent result by Ladd and Kavraki [2] shows that this process finds a path with h...

Path planning is one of the fundamental problems in games. The path planning problem can be defined as finding a collision-free path, traversed by a unit, between a start and goal position in an environment with obstacles. The variant we study is the problem of finding paths for one or more groups of units, such as soldiers or tanks in a real-time strategy game, all traversing the same (static)...

This paper presents in detail how the techniques described in my previous work [Kallmann et al., 2003] can be used for efficiently computing collision-free paths in a triangulated planar environment. The method is based on a dynamic Constrained Delaunay Triangulation (CDT) where constraints are the obstacles in the planar environment. The main advantage of relying on a triangulated domain is th...

The mobility sensors on a typical mobile robot vehicle have limited range. Therefore a navigation system has no knowledge about the world beyond this sensing horizon. As a result, path planners that rely only on this knowledge to compute paths are unable to anticipate obstacles sufficiently early and have no choice but to resort to an inefficient local obstacle avoidance behavior. To alleviate ...