Challenges persist in nonholonomic robot navigation for dynamic environments. This paper presents a framework for nonholonomic robot navigation in dynamic environment based on the model of Generalized Velocity Obstacles (GVO). The idea of velocity obstacles has been well studied and developed for obstacle avoidance since proposed in 1998. Though proved to be successful, most studies assume equa...

This paper proposes real time wireless remote control of robot dual arms and hands using IMUs (Inertial measurement unit). The remote control system is developed for robots to learn various complex tasks from operator’s demonstration. The control system helps robots to make human-like motion planning directly through operator’s demonstration rather than the RRT (Rapidly-Exploring Random Tree) a...

Rapidly-exploring random trees (RRTs) are data structures and search algorithms designed to be used in continuous path planning problems. They are one of the most successful state-of-the-art techniques as they offer a great degree of flexibility and reliability. However, their use in other search domains has not been thoroughly analyzed. In this work we propose the use of RRTs as a search algor...

We propose HRA*, a new randomized path planner for complex 3D environments. The method is a modified A* algorithm that uses a hybrid node expansion technique that combines a random exploration of the action space meeting vehicle kinematic constraints with a cost to goal metric that considers only kinematically feasible paths to the goal. The method includes also a series of heuristics to accele...

Sampling-based algorithms for path planning have achieved great success during the last 15 years, thanks to their ability to efficiently solve complex high-dimensional problems. However, standard versions of these algorithms cannot guarantee optimality or even high-quality for the produced paths. In recent years, variants of these methods, taking cost criteria into account during the exploratio...