Anytime sampling-based methods are an attractive technique for solving kino-dynamic motion planning problems. These algorithms scale well to higher dimensions and can efficiently handle state control constraints. However, intelligent exploration strategy is required accelerate their convergence avoid redundant computations. Using ideas from reachability analysis, this work defines a “Time-Infor...

In free-floating mode, space manipulator systems have their thrusters off, and exhibit nonholonomic behavior due to angular momentum conservation. The system is underactuated and a challenging problem is to control both the end effector location and the base attitude, using manipulator actuators only. Here, a path planning methodology satisfying this double goal is presented. The key idea is to...

This paper presents a new approach to path planning for robots with many degrees of freedom (dof) operating in known static environments. The approach consists of a preprocessing and a planning stage. Preprocessing, which is done only once for a given environment, generates a network of randomly, but properly selected, collision-free conngurations (nodes). Planning then connects any given initi...

Motion planning is studied in a time-varying environment. Each obstacle is a convex polygon that moves in a fixed direction at a constant speed. The robot is a convex polygon that is subject to a speed bound. A method is presented to determine whether or not there is a translational collision-free motion for a polygonal robot from an initial position to a final position, and to plan such a moti...

Robots on ships have to endure large inertial forces due to the non-inertial motion of the ship. The ship motion affects both the motion planning and control of the manipulator, and accurate predictions can improve performance substantially. It is thus important to investigate to what extent it is possible to predict the future motion of a ship. Based on these predictions, this paper presents a...

The paper presents the electronic design and motion planning of a robot based on decision making regarding its straight motion and precise turn using Artificial Neural Network (ANN). The ANN helps in learning of robot so that it performs motion autonomously. The weights calculated are implemented in microcontroller. The performance has been tested to be excellent.

1 Overview This work introduces a new incremental construction procedure for the generalized Voronoi diagram (GVD), the locus of points equidistant to two obstacles. This procedure is incremental in that it requires line of sight information (see Figure 4) to construct the GVD. Note that this notion of incremental is di erent from previous de nition of incremental where the GVD is constructed b...

We describe a process that constructs robot-specific circuitry for motion planning, capable of generating motion plans approximately three orders of magnitude faster than existing methods. Our method is based on building collision detection circuits for a probabilistic roadmap. Collision detection for the roadmap edges is completely parallelized, so that the time to determine which edges are in...

This paper presents an approach of motion planning for a humanoid robot using a state transition method. In this method, motion planning is simplified by introducing a state-space to describe the whole motion series. And each state in the state-space corresponds to a contact state specified during the motion. The continuous motion is represented by a sequence of discrete states. The concept of ...