Abstract Arbitration is a legal promise between the contracting parties, and they should hold their promises. If there any breach of that or attempt to breach, violating party bear outcomes. Upon an arbitration agreement, remedies become more crucial than ever refrain other from commencing parallel court proceedings. Together with stay damages, seeking effective remedy may benefit anti-suit inj...

The sampling based motion planning algorithm known as Rapidly-exploring Random Trees (RRT) has gained the attention of many researchers due to their computational efficiency and effectiveness. Recently, a variant of RRT called RRT* has been proposed that ensures asymptotic optimality. Subsequently its bidirectional version has also been introduced in the literature known as Bidirectional-RRT* (...

The paper presents a navigation algorithm for dynamic, uncertain environment. The static environment is unknown, while moving pedestrians are detected and tracked on-line. The planning algorithm is based on an extension of the Rapidly-exploring Random Tree algorithm, where the likelihood of the obstacles trajectory and the probability of collision is explicitly taken into account. The algorithm...

Chapter 1 and 2 of [Lat91]: Chapter 1 is an overview of motion planning and some overview of planning algorithms, such as Roadmap, Cell Decomposition and Potential field. Chapter 2 gives mathematical description about configuration space and obstacles, especially about the manifold structure of configuration space (embedding, parameterization, chart, atlas, connectedness, path, metric definitio...

This work presents an approach to learn path planning for robot social navigation by demonstration. We make use of Fully Convolutional Neural Networks (FCNs) to learn from expert’s path demonstrations a map that marks a feasible path to the goal as a classification problem. The use of FCNs allows us to overcome the problem of manually designing/identifying the cost-map and relevant features for...

This paper presents an improved method for planetary rover path planning in very rough terrain, based on the particle-based Rapidly-exploring Random Tree (pRRT) algorithm. It inherits the benefits of pRRT, an improvement over the conventional RRT algorithm that explicitly considers uncertainty in sensing, modeling, and actuation by treating each addition to the tree as a stochastic process. Alt...

This paper introduces the Information-rich Rapidly-exploring Random Tree (IRRT), an extension of the RRT algorithm that embeds information collection as predicted using Fisher Information Matrices. The primary contribution of this algorithm is target-based information maximization in general (possibly heavily constrained) environments, with complex vehicle dynamic constraints and sensor limitat...

This paper proposes the use of a randomized kinodynamic planning technique to synthesize dynamic motions for cable-suspended parallel robots. Given two mechanical states of the robot, both with a prescribed position and velocity, the method attempts to connect them by a collision-free trajectory that respects the joint and force limits of the actuators, keeps the cables in tension, and takes th...

ion-guided Sampling for Motion Planning University of New Hampshire Department of Computer Science Technical Report 12-01 Scott Kiesel, Ethan Burns and Wheeler Ruml May 1, 2012 Abstraction-guided Sampling for Motion Planningion-guided Sampling for Motion Planning Scott Kiesel and Ethan Burns and Wheeler Ruml Abstract Motion planning in continuous space is a fundamental robotics problem that has...

Sampling-based algorithms have become the favored approach for solving path and motion planning problems due to their ability to successfully deal with complex high-dimensional planning scenarios. This thesis presents an overview of existing sampling-based path planning methods for tree-structured rigid robots. The two most prominent algorithm families, Rapidly-exploring Dense Trees and Probabi...