On Using Passive RFID Tags to Control Robots for Path Following

Abstract

Although very few robots actually go to Mars, we continue to design these machines as if they were organisms operating in a totally unknown and hostile environment. In fact, in most situations, the environment is not only predictable, but it can also be manipulated so that the missions of the autonomous robot may be supported, by including sensors, actuators, computing and communication equipment. One of the most convenient ways to manipulate the environment is to deploy a number of RFID devices, capable of storing a variety of digital data, aimed to provide autonomous robots with valuable navigation information. As a result, the on-board equipment can be significantly reduced, along with the power requirements, and the overall cost of the robots. While the vast majority of the applications of the RFID technology for robot control are related to robot localization and mapping, this paper presents an experiment aimed to demonstrate the possibility of using RFID tags for path following.

Implementation of Context-Aware Based Robot Control System for Automatic Postal Logistics

“…Generally a robot manipulator only conducts the same operation repeatedly [2]. It usually operates a process, which is a preprogrammed process according to standard size of products [3]. However, we cannot use the existing robot manipulator for automated parcel sorting because parcels have various shapes and different sizes.…”

Engineering Human Stigmergy

“…Though interesting, the experiments described in [20] and [21] are limited to controlling individual agents, and do not make use of the capability of pheromones to mediate stigmergic interactions. The following use cases focus on human stigmergy.…”

“…By manipulating the pheromone maps it is possible to define easy-to-follow robot paths, by means of virtual pheromone gradients, as shown in figure 3. The idea was later used in an experiment for creating mixed robot formations with physical and virtual agents [21]. In this experiment, a real robot was programmed to follow a software simulated leader robot.…”

Using Particle Filters to Find Free Obstacle Trajectories for a Kinematic Chain

“…Many automated processes today require to solve the problem of planning a set of movements for an articulated arm with the objective of reaching a specific goal and avoiding obstacles without using neither sensors nor other technologies [15], but knowing its spatial information. These articulated arms are formally designated as kinematic chains.…”