For Students

Proposed topics for MSc thesis projects are detailed in the following. Additional topics to be developed in conjunction with companies are also available (contact your lecturer to have additional information).


Localisation and local planning for mobile robots

Localisation and local planning are two important parts of a mobile robot navigation system.
The first one is in charge of localising the robot in the environment, i.e., estimating its pose, the second one uses this estimate to control the robot so that it follows a desired path/trajectory.
Though localisation and local planning are tightly interacting, they are usually studied and implemented as two separated blocks.

The aim of this work is to study the possible interactions between the two subsystems, and to create a new navigation framework where localisation and local planning tightly interact, helping each other, in order to increase the safety and performance of the navigation system.

The work include a methodological part (theoretical analysis and redesign of the localisation/control systems), and a validation of the navigation system in simulation or an experimental validation.

Contact: Prof. Luca Bascetta


Development of a Modelica package for modeling and simulation of discrete event systems

The object-oriented language Modelica, designed for the modeling and simulation of complex engineering systems, is essentially based on the description of continuous-time dynamic phenomena, but still allows an accurate description of events, i.e. discontinuous variations. On the other hand, the design of engineering systems is initially based on functional descriptions, to which a discrete events modeling approach is applied. Exploiting the language mechanism for event management and applying appropriate theoretical formalisms (time Petri nets), the thesis will have as its objective the design and implementation of a Modelica package for modeling and simulation of discrete event systems, naturally integrated with the description of the continuous dynamics of the process. Application to an experimental production system is envisaged.

Contact: Prof. Gianni Ferretti


Online identification of cornering stiffnesses

In a previous thesis work, the problem of offline estimation of a vehicle’s cornering stiffnesses was tackled by an LFT (Linear Fractional Transform) reformulation of the single track model and the subsequent application of a maximum likelihood method. The good results obtained suggested the extension of the approach to an online estimate. The thesis work will therefore have as objective the implementation of the online estimation method, considering both an experimental type vehicle and, possibly, a suitably instrumented real vehicle.

Contact: Prof. Gianni Ferretti


Autonomous navigation in human crowded scenarios

Thesis proposals are available on the design of autonomous navigation algorithms, including local and global planning, for personal mobility devices in human crowded scenarios.
The aim is to design an autonomous navigation system that allows a personal mobility device (or a robot) to be perceived as socially acceptable.
This implies that the trajectories planned and followed by the vehicle should be as much as possible human like, and social constraints, like proxemics, should be enforced.
The works include a methodological part (theoretical analysis and design of the control system), and an experimental part (on a commercial electric wheelchair).

Contact: Prof. Luca Bascetta


Autonomous car control

Thesis proposals are available in the area of autonomous car control, mainly, but not only, focusing on the following topics: trajectory tracking control systems for driving a car at the limits of handling, lane-change stabilisation (system analysis and advanced control design).
The aim is to design control systems for controlling vehicles at the limits of handling, either in order to support autonomous driving or to increase safety of human-driven vehicles during emergency manoeuvres.
The works include a methodological part (theoretical analysis and design of the control system), and an experimental part (on a scaled car model).

Contact: Prof. Luca Bascetta


Multiple robot motion planning with communication constraints

 

The goal of this thesis is to develop a motion planning algorithm (for example based on sampling-based planning methods) to compute a coordinated path for multiple robots such that the robots always stay within a connection range with at least another one to transmit/receive information.
We also consider a specific scenario where there are two different groups of robots: while the first group of robots need to execute an assigned task (for example surveillance), the second group needs to behave as a relay between the first group of robots and a decision centre.

Contact: Prof. Luca Bascetta


 

Calculation of working sequences for double-head wire bending machines

 

In the metalworking industry a very important part concerns the modeling of metal wires, or rods, which, through successive bends, make it possible to create numerous objects for the most disparate uses. The bending of the wire takes place through specialized machinery, which can bend metal rods up to 10 mm in diameter with extreme ease, thanks to the versatility of the variable bending radius. The thesis work therefore has as its objective the determination, automatically, of all the admissible bending sequences, that is, without collisions with the machine components and with the wire itself, given the geometry of the piece to be made. The developed solution is based on the modeling of the geometric configuration assumed by the wire during processing as a manipulator with cylindrical links, whose configuration, in fact, evolves during the manufacturing process. The complexity of the task grows considerably in the case of a double-head machine, that is equipped with two folding devices on both ends of the wire.

Contact: Prof. Gianni Ferretti


 

 

Flexible collaborative assembly: multiple products

 

We have already developed a method for flexible task allocation and scheduling in a collaborative robotic cell. However the optimization in case of multiple products can become computationally intensive.

Can we learn an intelligent policy to determine which product to start at any time?

Contact: Prof. Paolo Rocco or Prof. Andrea Maria Zanchettin


 

Applications and case studies in collaborative robotics

 

The MERLIN Lab has been active for several years in research on human-robot interaction and collaborative robotics

A spin-off company, Smart Robots, has been recently created. It will bring a new device for human-robot collaboration to the market.

Theses will be available on development of case studies and applications of collaborative robotics with different robotic platforms.

Contact: Prof. Paolo Rocco or Prof. Andrea Maria Zanchettin


 

Soft bodies grasping modelling

 

The modelling of soft bodies can be done using different physics engines, but this functionality is unfortunately unavailable in robotics simulation platforms.

The purpose  of this project is to model soft bodies with particular attention to clothes and their interaction with grippers. We aim to import the relevant module as a plugin or develop our own.

Contact: Prof. Paolo Rocco or Prof. Andrea Maria Zanchettin


 

Human-robot collaboration control based on passive velocity field control and MPC

 

This thesis aims to define a safe controller for physical human-robot collaboration. Based on passive velocity field controller, MPC techniques will be applied to define the reference for the lower level controller, actively assisting and collaborating with the human.
An interaction dynamics model aiming to predict the collaboration state will be design and exploited by the MPC. The proposed controller will be stable, while empowering the human.
Work with a FRANKA robot for the experimental evaluation of the proposed approach.

Thesis to be developped at USI/SUPSI IDSIA, Manno (Switzerland)

Contact: Prof. Paolo Rocco or Prof. Andrea Maria Zanchettin


 

AI techniques for interaction control under dynamics uncertainty

 

Manipulators have to identify the context in which they are working, adapting their controller to the properties of the environment. However, it is not possible to tune a controller for each working scenario. Therefore, the manipulator has to implement a procedure to autonomously identify the working conditions and tune its controller consequently.
Artificial intelligence plays a fundamental role in such a field. The presented thesis aims to define a machine learning approach in order to give such degree of autonomy to the manipulator, being able to face unforeseen situations adapting it controller.
Work with a FRANKA robot for the experimental evaluation of the proposed approach.

Thesis to be developped at USI/SUPSI IDSIA, Manno (Switzerland)

Contact: Prof. Paolo Rocco or Prof. Andrea Maria Zanchettin


 

Intelligent task learning and optimization through minimum human demonstration

 

Robots are nowadays required to learn tasks quickly, adapting to uncertainties. Learning has to be efficient, requiring minimum trials and iterations.In order to efficiently teach a task to a manipulator exploiting human demonstrations, this thesis aims to investigate artificial intelligence techniques.
Reinforcement learning will be applied in order to quickly learn a specific task. In addition, control techniques will guarantee that the compensation of task uncertainties will be faced, maintaining active the robot learning capabilities.
Work with a FRANKA robot for the experimental evaluation of the proposed approach.

Thesis to be developped at USI/SUPSI IDSIA, Manno (Switzerland)

Contact: Prof. Paolo Rocco or Prof. Andrea Maria Zanchettin


 

Haptic-guided shared control tele-manipulation

 

Tele-manipulation causes a high cognitive load on the operator
Autonomous system are not sufficiently trusted by conservative industries.
Haptic-guide teleoperation (HGT) aims at making teleoperation easier
It is proofed HGT significantly reduces the cognitive load on human operator.

Thesis to be developped at the University of Lincoln (UK)

Contact: Prof. Paolo Rocco or Prof. Andrea Maria Zanchettin


 

Learning the robot controller from samples

 

Controlling a robot in a complex environment or to perform a difficult task is cumbersome.
These tasks are still performed via teleoperation.
AI can be used a full (or partial) model for the controller.
This project involves Deep time series to learn a complex task.
E.g., we have prepared a dataset of needle insertion task in robotic surgery context. We aim at learn the controller which performs this task using Deep time series, e.g. Recurrent Convolutional Neural Network or Long Short Term Memory.

Thesis to be developped at the University of Lincoln (UK)

Contact: Prof. Paolo Rocco or Prof. Andrea Maria Zanchettin


 

Application of an industrial numerical controller to the control of the model of a machine tool

 

Starting from an existing work, the goal of the thesis is the creation of a software that manages the flow of information and the simulation settings of the entire machine tool controlled by the same numerical controller installed on real machines. The machine tool model has been developed in Simcenter Amesim, and includes the description of the structural flexibility, thanks to Simcenter 3D, belonging to the same Suite. The VNCK (Virtual NC Kernel) software allows the execution of a complete Simunerik 840D numerical controller on a PC. Starting from a first version of a Supervisor, connecting the numerical controller and the simulation model, we want to create a software that can manage the virtualization of a machine tool as completely as possible, from the initialisation of the control system to the management of the machine model and possibly of the process, up to complete co-simulation. Given the great interest of the companies, it is intended to include at least one industrial case study proposed directly by interested parties in the experience.

Contact: Prof. Gianni Ferretti