Deep reinforcement learning has produced many success stories in recent years. Some
example fields in which these successes have taken place include mathematics, games …

Mobile robot path planning involves designing optimal routes from starting points to
destinations within specific environmental conditions. Even though there are well …

Reinforcement learning with safety constraints is promising for autonomous vehicles, of
which various failures may result in disastrous losses. In general, a safe policy is trained by …

Motion planning is critical to realize the autonomous operation of mobile robots. As the
complexity and randomness of robot application scenarios increase, the planning capability …

Mobile robots contributed significantly to the intelligent development of human society, and
the motion-planning policy is critical for mobile robots. This paper reviews the methods …

Distributed, scalable, and safe control of large-scale multi-agent systems is a challenging
problem. In this paper, we design a distributed framework for safe multi-agent control in …