Flocking control of Amigobots with Newton's method

Flocking Control of Mobile Robots with Obstacle Avoidance Based on Simulated Annealing Algorithm

“…With the aforementioned designed potential functions V i α and V i β , the flocking control problem of the mobile robot is considered as an optimization problem in this paper. In [33], Cheng et al designed a flocking control law that can drive the agents to evolve into the flock centering state. Motion control laws are proposed to synchronize the velocities and orientation angles via the Newton method in an environment without obstacles.…”

“…where Θ i is the orientation space of robot i, t k is the sample period, θ * i is the optimal orientation angle which has the maximal extent of the gradient descent of V i at t k . Due to that the space Θ i is continuous, methods based on the gradient descent are generally adopted [30,33]. Methods based on the random search algorithm provide another dependable solution.…”