Machine learning (ML) is a branch of artificial intelligence that has been developing at a
dynamic pace in recent years. ML is also linked with Big Data, which are huge datasets that …

The multimodal perception of intelligent robots is essential for achieving collision-free and
efficient navigation. Autonomous navigation is enormously challenging when perception is …

Non-learning based motion and path planning of an Unmanned Aerial Vehicle (UAV) is
faced with low computation efficiency, mapping memory occupation and local optimization …

This paper describes a hierarchical solution consisting of a multi-phase planner and a low-
level safe controller to jointly solve the safe navigation problem in crowded, dynamic, and …

This paper proposes a novel curriculum learning approach for collision avoidance using
feedback from the deep reinforcement learning (DRL) training process. Previous research …

Navigating safely and efficiently in dense crowds remains a challenging problem for mobile
robots. The interaction mechanisms involved in collision avoidance require robots to exhibit …

Home service robots prioritize cost-effectiveness and convenience over the precision
required for industrial tasks like autonomous driving, making their task execution more …

In recent years, Deep Reinforcement learning has made remarkable progress in various
application areas such as control of robots and vehicles, simulation, and natural language …

Robot navigation in a dynamic environment shared with humans is a challenging task.
Robot needs to process surrounding environmental data in real time and respond quickly …