Fabio Dalla Libera

About

Fabio Dalla Libera is a leading researcher in human-robot interaction and swarm robotics, whose work bridges intuitive programming and adaptive behavior. His most impactful contribution, the "Adaptive foraging for simulated and real robotic swarms: the dynamical response threshold approach" (106 citations), introduced a novel framework enabling robot collectives to dynamically adjust their foraging strategies based on environmental cues—a key advance for scalable, decentralized systems. Dalla Libera is also renowned for pioneering touch-based robot programming, as demonstrated in his highly cited papers "A new paradigm of humanoid robot motion programming based on touch interpretation" (14 citations) and "Teaching by touching" (14 citations), which allow users to intuitively edit humanoid motions by physically interacting with the robot, eliminating the need for technical expertise. His work on "Robots in education: New trends and challenges from the Japanese market" (18 citations) provides a comprehensive analysis of robotics kits used across educational levels in Japan, influencing curriculum design worldwide. Additionally, Dalla Libera has explored motor synergies for low-dimensional control of musculoskeletal robots and bystander robot actions in multiparty conversations. With over 185 total citations, his research continues to shape accessible, adaptive robotics for education, industry, and everyday life.

Research Focus

Key Achievements

Top Papers

1. 1
   Adaptive foraging for simulated and real robotic swarms: the dynamical response threshold approach

   106 citations · 2016
2. 2
   Robots in education: New trends and challenges from the Japanese market

   18 citations · 2013
3. 3
   A new paradigm of humanoid robot motion programming based on touch interpretation

   14 citations · 2009
4. 4
   Teaching by touching: An intuitive method for development of humanoid robot motions

   14 citations · 2007
5. 5
   Generation of Bystander Robot Actions Based on Analysis of Relative Probability of Human Actions

   9 citations · 2017
6. 6
   Learning humanoid soccer actions interleaving simulated and real data

   6 citations · 2007
7. 7
   Direct programming of a central pattern generator for periodic motions by touching

   6 citations · 2010
8. 8
   Extracting motor synergies from random movements for low-dimensional task-space control of musculoskeletal robots

   5 citations · 2015
9. 9
   Developing Robot Motions by Simulated Touch Sensors

   4 citations · 2008
10. 10
    Intuitive Humanoid Motion Generation Joining User-Defined Key-Frames and Automatic Learning

    3 citations · 2009

Key Collaborators

Contact & Links