Advanced Driving Assistance Systems for agricultural applications
Sara Furioli
PHD Student
DEIB - Conference Room "E. Gatti" (Building 20)
January 17th, 2023
11.30 am
Contacts:
Simone Formentin
Research Line:
Control systems
PHD Student
DEIB - Conference Room "E. Gatti" (Building 20)
January 17th, 2023
11.30 am
Contacts:
Simone Formentin
Research Line:
Control systems
Abstract
On January 17th, 2023 at 11.30 am Sara Furioli, PHD Student, will give a seminar on "Advanced Driving Assistance Systems for agricultural applications" in DEIB Conference Room.
Autonomous navigation of agricultural vehicles is particularly appealing to industry due to its potential to meet the strict requirements on precision imposed by sensitive procedures like seeding or pruning, and to reduce man's workload, by easing the operator from the driving task so that he/she can focus on the ongoing agricultural procedure. Meanwhile, the problem is still very interesting from the research point of view, since the high precision requirements must be achieved in a complex and continuously changing environment, with reduced maneuvering space, while working on high-value cultivation. In this scenario, vehicle global localization is still an open issue: GNSS technology is not always reliable as thick vegetation may cause signal loss. Relative-row localization is also essential and cannot be done using maps because they should be constantly updated due to the pronounced dynamism of the environment. Planning a local path is not a straightforward task, either: the vehicle must follow a global route dictated by the agricultural procedure, while adapting it to growing vegetation and the presence of other obstacles. My research aims at investigating the above-mentioned issues through the use of different technologies, and approaching the problem at different automation levels.
Autonomous navigation of agricultural vehicles is particularly appealing to industry due to its potential to meet the strict requirements on precision imposed by sensitive procedures like seeding or pruning, and to reduce man's workload, by easing the operator from the driving task so that he/she can focus on the ongoing agricultural procedure. Meanwhile, the problem is still very interesting from the research point of view, since the high precision requirements must be achieved in a complex and continuously changing environment, with reduced maneuvering space, while working on high-value cultivation. In this scenario, vehicle global localization is still an open issue: GNSS technology is not always reliable as thick vegetation may cause signal loss. Relative-row localization is also essential and cannot be done using maps because they should be constantly updated due to the pronounced dynamism of the environment. Planning a local path is not a straightforward task, either: the vehicle must follow a global route dictated by the agricultural procedure, while adapting it to growing vegetation and the presence of other obstacles. My research aims at investigating the above-mentioned issues through the use of different technologies, and approaching the problem at different automation levels.
