The advent of AlphaGo and its successors marked the beginning of a new paradigm in
playing games using artificial intelligence. This was achieved by combining Monte Carlo …

This paper provides a comprehensive review of the integration of advanced power
management systems and learning techniques in the field of robotics. It identifies the critical …

Recently, bio-inspired algorithms have been increasingly explored for autonomous robot
path planning on grid-based maps. However, these approaches endure performance …

In practice, many types of manipulation actions (eg, pick-n-place and push) are needed to
accomplish real-world manipulation tasks. Yet, limited research exists that explores the …

A combined task-level reinforcement learning and motion planning framework is proposed
in this paper to address a multi-class in-rack test tube rearrangement problem. At the task …

The rearrangement of objects is an essential task in daily human life. Subconsciously,
humans break down such tasks into three components: perception, reasoning, and …

Manipulating a target object using non-prehensile actions presents a complex problem that
requires addressing multiple constraints, such as finding collision-free trajectories, modeling …

Multiple ecological tactics, like the ones described here, can be imitated to strongly affect
these two components in the construction sector. This article provides an in‐depth …