Publications by Alcherio Martinoli

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Multi-robot systems can solve complex tasks that require the coordination of the team-member positions with respect to each other.While the development of ad-hoc relative positioning platforms embedding cheap off-the-shelf components is a practical choice, ...

We apply an adapted version of Particle Swarm Optimization to distributed unsupervised robotic learning in groups of robots with only local information. The performance of the learning technique for a simple task is compared across robot groups of various ...

Water as a medium poses a number of challenges for robots, limiting the progress of research in underwater robotics vis-a-vis ground or aerial robotics. The primary challenges are satellite based positioning and radio communication being unusable due to hi ...

Unmanned Aerial Vehicles (UAVs) are becoming a significant field of research with numerous applications, ranging from mapping to surveillance. New applications, such as aerial delivery of goods, are expected to appear in the next years and will require mor ...

Designing effective behavioral controllers for mobile robots can be difficult and tedious; this process can be circumvented by using online learning techniques which allow robots to generate their own controllers online in an automated fash- ion. In multi- ...

This work is situated in the context of collaboratively solving the localization problem for unknown initial conditions. We address this problem with a novel, fully decentralized, real-time particle filter algorithm, designed to accommodate realistic robot ...

This paper proposes a generalized method for tracking of multiple objects from moving, cooperative vehicles -- bringing together an Unscented Kalman Filter for vehicle localization and extending a Sequential Monte Carlo Probability Hypothesis Density filte ...

In this work, we address the design of tightly integrated control, estimation, and allocation algorithms allowing a group of robots to move collectively. For doing so, we leverage a modular framework that allows us to define precisely the needed functional ...

In this paper, we state, using thorough mathe- matical analysis, sufficient conditions to perform a rendezvous maneuver with a group of differential-wheeled robots endowed with an on-board, noisy, local positioning system. In particular, we extend the exis ...

Model-based synthesis of distributed controllers for multi-robot systems is commonly approached in either a top-down or bottom-up fashion. In this paper, we investigate the experimental challenges of both approaches, with a special emphasis on resource-con ...

We propose two contrasting approaches to the scalable distributed control of a swarm of self-assembling miniaturized robots, specifically the formation of chains of a desired length: (1) a deterministic controller in which robots communicate with each othe ...

Simulation is frequently used in the study of multi-agent systems. Unfortunately, in many cases, it is not necessarily clear how faithfully the details of the simulated model represent the behavior of the physical system. Often, the effects of the environm ...

Static and mobile sensor nodes can be employed in gas monitoring tasks to detect gas leaks in an early stage and localize gas sources. Due to the intermittent nature of gas plumes and the slow dynamics of commonly used gas sensors, measuring gas concentrat ...

We present an adaptive strategy for a group of robots engaged in the localization of multiple targets. The robotic search algorithm is inspired by chemotaxis behavior in bacteria, and the algorithmic parameters are updated using a distributed implementatio ...

This work is developed in the framework of Institutional Robotics (IR), an approach to cooperative distributed robotic systems that draws inspiration from the social sciences. We consider a case study concerned with a swarm of simple robots which has to ma ...

Wireless radios are a great consumer of energy in sensor networks. Retrieving data from a remote deployment in an energy-efficient fashion is a difficult problem, and while solutions have been proposed in literature, real-world systems typically implement robust though inefficient methods. In an effort to bring efficient monitoring techniques to real-world environmental sensor networks, we seek to now quantify the performance brought by these algorithms in practical terms, i.e., by their resulting reduction

This paper addresses qualitative and quantitative diversity and specialization issues in the frame- work of self-organizing, distributed, artificial systems. Both diversity and specialization are obtained via distributed learning from initially homogeneous swarms. While measuring diversity essentially quantifies differences among the individuals, assessing the degree of specialization implies to correlate the swarm’s heterogeneity with its overall performance. Starting from a stick-pulling experiment in col

The ability to move in complex environments is a fundamental requirement for robots to be a part of our daily lives. While in simple environments it is usually straightforward for human designers to foresee the different conditions a robot will be exposed ...

In this letter, we propose an adaptive risk-based replanning strategy in the context of multirobot task allocation for dealing with limitations of local perception and unpredicted human behavior. Our replanning method is based on the variations of social r ...

The last decade has seen a growing interest in air quality monitoring using networks of wireless low-cost sensor platforms. One of the unifying characteristics of chemical sensors typically used in real-world deployments is their slow response time. While ...

Alcherio Martinoli

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Two-Phase Online Calibration for Infrared-based Inter-Robot Positioning Modules

Multi-Robot Learning with Particle Swarm Optimization

Easily Deployable Underwater Acoustic Navigation System for Multi-Vehicle Environmental Sampling Applications

3D Collision Avoidance Algorithm for Unmanned Aerial Vehicles with Limited Field of View Constraints

Distributed Scalable Multi-Robot Learning using Particle Swarm Optimization

A Reciprocal Sampling Algorithm for Lightweight Distributed Multi-Robot Localization

Cooperative Multiple Dynamic Object Tracking on Moving Vehicles Based on Sequential Monte Carlo Probability Hypothesis Density Filter

A modular functional framework for the design and evaluation of multi-robot navigation

Bayesian Rendezvous for Distributed Robotic Systems

Top-Down vs Bottom-Up Model-Based Methodologies for Distributed Control: A Comparative Experimental Study

Comparing and modeling distributed control strategies for miniature self-assembling robots

Exploration of an Incremental Suite of Microscopic Models for Acoustic Event Monitoring Using a Robotic Sensor Network

Design and Evaluation of Modular Gas and Wind Sensing Nodes for Static and Mobile Deployments

Distributed Adaptation in Multi-Robot Search using Particle Swarm Optimization

An Experimental Study in Wireless Connectivity Maintenance Using up to 40 Robots Coordinated by an Institutional Robotics Approach

A Flexible In Situ Power Monitoring Unit for Environmental Sensor Networks

Diversity and Specialization in Collaborative Swarm Systems

The Effect of the Environment in the Synthesis of Robotic Controllers: A Case Study in Multi-Robot Obstacle Avoidance using Distributed Particle Swarm Optimization

Adaptive Risk-Based Replanning For Human-Aware Multi-Robot Task Allocation With Local Perception

Mitigating Slow Dynamics of Low-Cost Chemical Sensors for Mobile Air Quality Monitoring Sensor Networks