3 accepted papers
In this paper, we propose a framework based on velocity obstacles to address dynamic obstacle avoidance problem for constrained mobile robots. The framework establishes a nonlinear mapping from the control domain to the velocity space based on the robot’s kinematic model and input constraints. This
Sampling-based Model Predictive Control (MPC) algorithms such as Model Predictive Path Integral (MPPI) excel in managing nonlinear constraints and complex systems. However, their conventional sampling strategies often result in suboptimal local solutions. To address this problem, we propose RESM-MPP
In this letter, we propose a method for the navigation of swarm unmanned aerial vehicles (UAVs) in complex environments with obstacles. We propose an algorithmic framework based on Smoothed Particle Hydrodynamics (SPH). In this framework, each UAV is considered a particle, computing its motion infor