Abstract: This paper proposes a solution to the motion planning
and control problem of car-like mobile robots which is required to
move safely to a designated target in a priori known workspace
cluttered with swarm of boids exhibiting collective emergent
behaviors. A generalized algorithm for target convergence and
swarm avoidance is proposed that will work for any number of
swarms. The control laws proposed in this paper also ensures
practical stability of the system. The effectiveness of the proposed
control laws are demonstrated via computer simulations of an
emergent behavior.
Abstract: In this paper smooth trajectories are computed in the Lie group SO(2, 1) as a motion planning problem by assigning a Frenet frame to the rigid body system to optimize the cost function of the elastic energy which is spent to track a timelike curve in Minkowski space. A method is proposed to solve a motion planning problem that minimize the integral of the square norm of Darboux vector of a timelike curve. This method uses the coordinate free Maximum Principle of Optimal control and results in the theory of integrable Hamiltonian systems. The presence of several conversed quantities inherent in these Hamiltonian systems aids in the explicit computation of the rigid body motions.
Abstract: In this paper, we focus on the use of knowledge bases
in two different application areas – control of systems with unknown
or strongly nonlinear models (i.e. hardly controllable by the classical
methods), and robot motion planning in eight directions. The first
one deals with fuzzy logic and the paper presents approaches for
setting and aggregating the rules of a knowledge base. Te second one
is concentrated on a case-based reasoning strategy for finding the
path in a planar scene with obstacles.
Abstract: This paper presents a wrap-around view system with 4
smart cameras module and remote motion mobile robot control equipped with smart camera module system. The two-level scheme for
remote motion control with smart-pad(IPAD) is introduced on this
paper. In the low-level, the wrap-around view system is controlled or operated to keep the reference points lying around top view image
plane. On the higher level, a robot image based motion controller is utilized to drive the mobile platform to reach the desired position or
track the desired motion planning through image feature feedback. The
design wrap-around view system equipped on presents such advantages as follows: 1) a satisfactory solution for the FOV and affine
problem; 2) free of any complex and constraint with robot pose. The performance of the wrap-around view equipped on mobile robot
remote control is proven by experimental results.
Abstract: This paper presents a new sensor-based online method for generating collision-free near-optimal paths for mobile robots pursuing a moving target amidst dynamic and static obstacles. At each iteration, first the set of all collision-free directions are calculated using velocity vectors of the robot relative to each obstacle and target, forming the Directive Circle (DC), which is a novel concept. Then, a direction close to the shortest path to the target is selected from feasible directions in DC. The DC prevents the robot from being trapped in deadlocks or local minima. It is assumed that the target's velocity is known, while the speeds of dynamic obstacles, as well as the locations of static obstacles, are to be calculated online. Extensive simulations and experimental results demonstrated the efficiency of the proposed method and its success in coping with complex environments and obstacles.