Teaching robots to manipulate objects with humanlike dexterity has long been one of robotics' toughest challenges. Tasks such as rotating an object in-hand or coordinating two robot arms to maneuver a ...

Abstract: Rapidly-exploring random tree star (RRT*) has attracted intensive attention in track planning due to its asymptotic optimal properties. However, the RRT* algorithm plans costly trajectory ...

Autonomous driving technology primarily includes four aspects: environmental perception, behavior decision-making, path planning and motion control. Among these, path planning is a key technology that ...

With the rapid development of autonomous driving technology, path planning has gained significant attention as it holds great potential for improving safety. The Rapidly-exploring Random Tree star(RRT ...

With the rapid development of artificial intelligence, computer vision, and sensor technologies, robotics have witnessed remarkable progress over the years. However, a significant challenge modern ...

Imagine you visit a maze with some friends. You emerge from the exit shortly after going in, and wait around for hours before your friends emerge. Naturally, they ask about the path you took — surely ...

With the advance in algorithms, deep reinforcement learning (DRL) offers solutions to trajectory planning under uncertain environments. Different from traditional trajectory planning which requires ...

Abstract: This paper proposes a path planning algorithm using the hybridization of the rapidly-exploring random tree (RRT) and ant colony system (ACS) algorithms. The RRT algorithm can quickly ...

Control and Systems Department, University of Technology-Iraq, Baghdad, Iraq. Path planning is a process of obtaining reasonable, collision free route between start and goal point, where the need for ...

The inability of glasses to find their lowest-energy configurations is often attributed to their potential energy landscapes: rugged, barrier-filled surfaces in high-dimensional space that seem ...