Call for Invited Sessions

Zheng Chen, Zhejiang University, China
Lei Qiao, Shanghai Jiao Tong University, China
Umar Farooq, University of the Punjab Lahore, India

Abstract: For the purpose of developing and utilizing the ocean, the underwater robots play important roles and have attracted increasingly attention in recent years. The underwater robots mainly include the ROV AUV, underwater glider, underwater manipulator, etc., and are widely used in the underwater resource exploration, search and rescue, environmental monitoring and other related tasks. The main issue to achieve the above tasks is the motion control of underwater robots. However, due to the diverse structure of underwater robots and complicated underwater environment, the motion control still faces many challenges (e.g., nonlinearity, uncertainties, underactuated characteristics, time-varying environmental disturbance, etc.), but the current control design mostly based on the linear PID method, which cannot ensure the precise operation performance. Therefore, the advanced and intelligent control design is desired to achieve better operation performance of underwater robots and overcome the challenges such as the nonlinearity, uncertainties, underactuated characteristics and time-varying environmental disturbance.

Gregor Klančar, University of Ljubljana, Faculty of Electrical Engineering,
Slovenia
Marija Seder, University of Zagreb Faculty of Electrical Engineering and Computing, Croatia

Abstract: Modern manufacturing and warehousing systems are facing the challenges of the market, which dictates increasingly personalized products, low manufacturing costs, unconditional quality, and the achievement of ever more demanding logistic objectives.  Important part of intralogistics are also autonomous transport vehicles where several good solutions are already implemented. However, several challenges and improvements are still possible to increase production flexibility and efficiency. Some of them are: automatic creation and adaptation of map and layout configurations, multiagent path planning, coordinated route planning and control for a group autonomous transportation robots, increased intelligence of task assignment rules that can adapt to current situations, local agent and multiagent agent conflicts solving with tasks related to path planning, trajectory tracking, control, obstacle avoidance approaches, reinforcement learning, simulations and the like.

November 30, 2021 December 13, 2021

December 15, 2021