Humanoid robots are emerging as a new technology for industrial applications, with companies racing to commercialize them by 2025. This article provides an in-depth analysis of the current state of the humanoid robot market, the technical challenges, and the key considerations for successful deployment in industrial environments.
This paper proposes a new nonlinear adaptive learning controller, NLVG-PID, that is low-cost and portable to different quadcopter platforms to enable effective obstacle avoidance during delivery drone missions.
The core message of this paper is that a combination of Behavior Trees (BTs) and Finite State Machines (FSMs) can be an effective solution for implementing task-switching policies in complex industrial applications, such as automating the explosive charging process in underground mines.