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 ...

This work considers the computational costs associated with the implementation of a failure-tolerant path planning algorithm proposed in [1]. The algorithm makes the following assumptions: a manipulator is redundant relative to its task, only a single joint failure occurs at any given time, the manipulator is capable of detecting a joint failure and immediately locks the failed joint, and the e...

This paper addresses validation of a curvature-theory-based time-invariant inverse kinematic model and a related tracking algorithm for human motor control of reaching motions. Human subjects made unconstrained reaching motions in the horizontal plane to fixed targets at three self-selected speeds. Consistent shoulder/elbow joint speed ratios for motions to the same target across speeds were ob...

Space robots are an effective resource for astronauts working in a dangerous space environment. This paper proposes and implements a system to validate the performance of robot movement in space. A humanoid robot was designed with a vision-based self-calibration and navigation system. In addition, a path planning method was proposed to minimize joint torque. Simple gravity-compensation equipmen...

Robot controller design is usually hierarchical with both high-level task and motion planning and low-level control law design. In the presented works, we investigate methods for low-level and high-level control designs to guarantee joint performance of human-robot interaction (HRI). In the first work, a low-level method using the switched linear quadratic regulator (SLQR), an optimal control p...

This paper presents a novel kind of generalizing neural storage tailored for the problem of global motion planning for six-joint manipulators in complex, changing environments. Paths are stored in a growing map of neurons with adaptive ellipsoidal receptive eld, called the Ellipsoidal Map. Path planning is based on nding the best-matching neurons for start and goal and a graph search in the neu...