Ali Abdul Khaliq

Towards real-world gas distribution mapping and leak localization using a mobile robot with 3d and remote gas sensing capabilities

Due to its environmental, economical and safety implications, methane leak detection is a crucial task to address in the biogas production industry. In this paper, we introduce Gasbot, a robotic platform that aims to automatize methane emission monitoring in landfills and biogas production sites. The distinctive characteristic of the Gasbot platform is the use of a Tunable Laser Absorption Spectroscopy (TDLAS) sensor. This sensor provides integral concentration measurements over the path of the laser beam. Existing gas distribution mapping algorithms can only handle local measurements obtained from traditional in-situ chemical sensors. In this paper we also describe an algorithm to generate 3D methane concentration maps from integral concentration and depth measurements. The Gasbot platform has been tested in two different scenarios: an underground corridor, where a pipeline leak was simulated and in a decommissioned landfill site, where an artificial methane emission source was introduced.

Stigmergic algorithms for multiple minimalistic robots on an RFID floor

Stigmergy is a powerful principle in nature, which has been shown to have interesting applications to robotic systems. By leveraging the ability to store information in the environment, robots with minimal sensing, memory, and computational capabilities can solve complex problems like global path planning. In this paper, we discuss the use of stigmergy in minimalist multi-robot systems, in which robots do not need to use any internal model, long-range sensing, or position awareness. We illustrate our discussion with three case studies: building a globally optimal navigation map, building a gradient map of a sensed feature, and updating the above maps dynamically. All case studies have been implemented in a real environment with multiple ePuck robots, using a floor with 1,500 embedded radio frequency identification tags as the stigmergic medium. Results collected from tens of hours of real experiments and thousands of simulated runs demonstrate the effectiveness of our approach.

Stigmergy at work: Planning and navigation for a service robot on an RFID floor

Many species in nature store information in the environment to facilitate the performance of tasks and enable cooperation. This principle is known as stigmergy. Stigmergy has been widely studied in robotic systems, but so far mostly in simulation or in laboratory proofs of concept. In this paper, we propose a stigmergic approach to goal-directed navigation that can be used for navigation of a full-scale robotic system in a real apartment. A team of small ePuck robots build a set of navigation maps directly onto an RFID floor, where each map is associated to one predefined goal. The information stored in the floor can then used by a mid-size robot or by a larger domestic robot to perform safe navigation toward the predefined goals. To navigate, robots only rely on the information read from the RFID tags: in particular, they do not need to use an internal map or to perform self-localization. This results in robust and repeatable navigation with minimal hardware and software requirements.

Inexpensive, reliable and localization-free navigation using an RFID floor

Stigmergy is a principle observed in nature, in which animals store in the environment information to be used for communication or navigation. Stigmergy has recently been exploited in robotics: simple robots store a goal distance field in read-write RFID tags embedded in the floor, and later follow the gradient of this field to navigate optimally to that goal. Stigmergic navigation is localization-free, since robots only rely on the values read from the tags and do not need to know their own location. This makes navigation inexpensive (no ranging sensors) and reliable (no localization failures). To make this approach viable in practice, two issues need to be addressed: how to simplify the installation of an RFID floor; and how to follow the field gradient in a reliable way. This paper presents solutions to both problems. The solutions are validated through experiments performed on simulated and on real robots.

Point-to-point safe navigation of a mobile robot using stigmergy and RFID technology

Reliable autonomous navigation is still a challenging problem for robots with simple and inexpensive hardware. A key difficulty is the need to maintain an internal map of the environment and an accurate estimate of the robots position in this map. Recently, a stigmergic approach has been proposed in which a navigation map is stored into the environment, on a grid of RFID tags, and robots use it to optimally reach predefined goal points without the need for internal maps. While effective, this approach is limited to a predefined set of goal points. In this paper, we extend this approach to enable robots to travel to any point on the RFID floor, even if it was not previously identified as a goal location, as well as to keep a safe distance from any given critical location. Our approach produces safe, repeatable and quasi-optimal trajectories without the use of internal maps, self localization, or path planning. We report experiments run in a real apartment equipped with an RFID floor, in which a service robot either reaches or avoids a user who wears slippers equipped with an RFID tag reader.

Children Playing with Robots Using Stigmergy on a Smart Floor

Reliable, safe interaction is essential when humans, robots move in close proximity. In this paper, we present a stigmergic approach where humans interact with robots via a smart floor. Stigmergy has been widely studied in robotic systems, however, HRI has thus far not availed itself of stigmergic solutions. We realize a stigmergic medium via RFID tags embedded in the floor,, use these to enable robot navigation, human tracking, as well as the interaction between robots, humans. The proposed method allows to employ robots with minimal sensing, computation capabilities. The approach relies only on the RFID sensors, the information stored in the tags,, no internal map is required for navigation. We design, implement a prototype game which involves a robot, a child moving together in a shared space. The prototype demonstrates that the approach is reliable, adheres to given safety constraints when human, robot are moving within close proximity of each other.