Abstract: In numerous cellular applications, cells are transported to specific positions or extracted from complex cell solutions. Therefore, an efficient cell transportation path planner for these ...
Aerospace and Mechanical Insider on MSN
Landmark-driven DRL boosts mobile robot navigation
Mobile robots are increasingly deployed in applications ranging from household cleaning to hazardous industrial inspection, ...
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 ...
Finding bipartite matchings is one of the oldest and most well-studied problems in computer science. This problem comes up in many guises, such as when matching donors to recipients for organ ...
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 ...
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