LASA

LASA develops method to enable humans to teach robots to perform skills with the level of dexterity displayed by humans in similar tasks. Our robots move seamlessly with smooth motions. They adapt on-the-fly to the presence of obstacles and sudden perturbations, mimicking humans’ immediate response when facing unexpected and dangerous situations.

Current highlights

Robotics at EPFL

Robotics at EPFL is an interfaculty initiative that connects and promotes EPFL’s advanced expertise
in robotics and autonomous systems. Check it out!

Learning for adaptive and reactive robot control

LASA teamed up with MIT press to publish a textbook presenting a wealth of machine learning techniques to make robot control more flexible and safer when interacting with humans.

Robotics Innovation Booster

The Innovation Booster Robotics, lead by Professor Aude Billard, is a program powered by the Swiss Innovation Agency, Innosuisse. Innovation Booster Robotics promotes knowledge transfer and sponsors co-operation with partners across robotics research labs and industry.

Videos highlight of research areas at LASA

Current project grants

EU DARKO

Dynamic agile robots that learn and optimize operations

Robetarme

Human-robot collaborative construction system for shotcrete

Microsurgery

Qualitative assessment of skills and skill acquisition in microsurgery

Past project grants

EU I.AM Project

From pick-and-place to grab-and-toss

Hasler Stiftung

Four-arms manipulation and applications to surgery

SAHR

ERC Advanced Grant: Skill acquisition in humans and robots (SAHR)

EU Crowdbot project

Safe navigation of robot in crowd

CHISTERA CORSMAL

Estimate the physical properties of objects for safe handover from / to humans

Swiss SNF – NCCR

Robotics National Center of Competence in Research

Secondhands

Creating a proactive robot assistant for maintenance tecnicians

EU CogIMon

A EU-funded research project for Cognitive Interactive Motion

Alterego

An EU funded project to work on humanoid robotics and virtual reality to improve social interactions