Advances in Robotics & Automation

Motion planning is a common task required to be fulfilled by robots. A novel strategy combining particle swarm optimization and gravity gradient inversion algorithm is proposed for motion planning of mobile robots. Particle Swarm Optimization (PSO) is employed to do motion planning and fitness function in PSO is built based on gravity gradient inversion algorithm. The relative distance and orientation between each particle and the center of an obstacle is calculated by gravity gradient inversion algorithm, then, a fitness function is built based on the distance and orientation. The proposed strategy is validated by the simulation and experiment results.

A lot of work has been done to track a moving object with the aid of a camera. This paper describes one such technique, which can constantly track and follow moving objects. Most of the work done in this paper was referred from the work done by Nazim. The camera is used as a feedback sensor to help the robot follow the object. The robot system is truncated into two sub-systems: vision and motion. The vision system comprises of a two-motor pan-tilt camera driving mechanism with embedded potentiometer sensor, PCI image acquisition board and PWM based DC motor driver board. The motion system is made up of a two-wheel and two-castor platform driven by servomotors with amplifiers. The system tries to demonstrate the eye tracking ability of a human when a moving object is in focus. The robot used for this purpose is Alice, the most recent model that was developed in the year 2002 has been chosen.