Reconfigurable Collaborative Agri-Robots (Recoaro)
In rugged, mountainous regions, like South Tyrol, many agricultural tasks are performed manually, which can lead to uncertainty in food production and cost, seasonal labor shortages, increased risk of fatal accidents, and adverse long-term health effects on farm workers. Alpine agricultural environments are complex and unstructured, limiting the use of autonomous systems. Further, most Alpine farms are relatively small and cannot afford the cost of several machines that are specialized for only one or two tasks. We aim to develop new methods that can enable agricultural robotic systems for Alpine farms to be modular, reconfigurable and semi-autonomous, combining automation with human input to create a collaborative, flexible, human-robot team. To achieve this goal, fundamental scientific advances are required in the areas of: kinematic/dynamic modelling, automatic control, trajectory planning, and shared human-robot control of modular reconfigurable robotic (MRR) platforms. Project objectives address the following open problems: 1) How to automatically adapt dynamic/kinematic models to capture the changing characteristics of MRRs as they are reconfigured? We will develop systematic methods to update the kinematics/dynamics using data stored in each module, accounting for model uncertainties using interval arithmetic. 2) How can model-based controllers for mobile MRRs be adapted as the underlying dynamic/kinematic models of the MRR change? We will develop new centralized control schemes for mobile MRRs using interval arithmetic to ensure robust stability and tracking performance. 3) MRRs can become highly redundant, complicating trajectory planning, but simplifying optimization. How can low-level problems (self-collision, joint-limit avoidance) and high-level problems (planning time/energy optimal trajectories) be solved as a task is executed? We will study how to extend task-prioritized redundancy resolution to MRRs for trajectory planning. 4) Few studies address the stability of shared human-robot control systems. We will explore if homogeneously rescaled shared control laws can be used to ensure the Lyapunov stability of MRRs. 5) In shared trajectory tracking control a human may periodically intervene and move the MRR towards a new trajectory. How should trajectory planning be handled when the human returns control to the robot? We will examine how to combine global and local trajectory planning for shared control using homogenous transformations. 6) Experimental validation of the methods developed will be conducted at the UniBZ FIeld Robotics South Tyrol (FIRST) Lab and at Fraunhofer Italia’s (FhI’s) Area for REsearch and iNnovative Applications (ARENA), both of which are located in the NOI Techpark. The experiments will simulate three common farming tasks: spraying, inspection and harvesting. The principal project participants are Profs. von Ellenrieder, Vidoni and Mazzetto (UniBZ), and Dr. Giusti (FhI).
SPRUCE-ROBOT: Smart PRUning and Climbing treEs ROBOT
The production of high value-added wood requires proper pruning during the life of a tree so that its trunk has a cylindrical shape and does not contain knots.
This project is an applied interdisciplinary research project that aims to apply mechatronic approaches for automating an important forestry activity, like tree pruning. Thanks to the cooperation with our external partner, the Azienda Demanio Provinciale, the main requirements for a novel mobile/climbing robotic prototype with pruning capabilities will be defined.
Thus, the interdisciplinary team will study, design and develop field robotics technologies and practices that can assist the forestry industry to produce timber more efficiently, more safely and with less waste.