Alessandro Palleschi

Hi! I'm Alessandro, currently a robotics Ph.D. student at the University of Pisa and former visiting researcher at the Stanford Artificial Intelligence Laboratory (SAIL), Stanford University. I am focused on developing innovative tools for planning and control of collaborative robots in interaction-rich unstructured environments. I work on autonomous manipulation and optimal trajectory planning for collaborative robots. My research combines the fields of robotics, artificial intelligence, and human-robot interaction to create solutions that enhance the capabilities of robots to work alongside humans and other autonomous agents. With a strong foundation in motion planning, grasping, and manipulation, I am committed to advancing the state-of-the-art in this field and creating more efficient and effective robotic systems.
I am also co-founder of XStar Motion, an innovative start-up which aims at transforming the way the motion of machines is planned.

If you want to know more about my research, projects, and publications, please follow the associated links.

As a Ph.D. candidate in Robotics and Automation at the University of Pisa’s Research Center "E. Piaggio", I have gained extensive experience developing planning and decision-making algorithms for collaborative robots working in unstructured environments. I have worked on various international industry-oriented research projects such as ILIAD, DARKO, and SOPHIA. I was responsible for designing, implementing, and testing planning algorithms for dexterous manipulation using a dual-arm robotic platform. Furthermore, I have developed grasp planning algorithms for robots equipped with rigid and compliant grippers and optimized trajectory planning algorithms to ensure safe and efficient operations of robots working alongside humans.
My work resulted in several publications on leading robotics journals, such as RA-L, RA-M, and T-ASE and on international conferences such as ICRA, IROS, CASE, and Humanoids.
Checkout my projects to know more about my research!

My research on optimal trajectory planning lead to the creation of XStar Motion, an innovative start-up which aims at transforming the way the motion of machines is planned.

We developed X*Solve, an algorithm that evaluates the optimal trajectory over a working-cycle path fulfilling the machine's velocity, acceleration and jerk limits. This software works online, providing the optimized references at the controller frequency, and is integrable on both robots and CNC machines.

XStar Motion fuses 20 years of automation expertise provided by EUROSOFT with cutting-edge research in motion planning and control conducted by leading researchers at University of Pisa.

Today AI theory, algorithms implementation, and computational power, allow to plan the motion of every machine to exploit its full power, and to update it for every single task, autonomously. Xstar Motion will bring this down to the automation industry.