LiftMeUp: Globally optimal algorithms for dexterous manipulation and locomotion

Robots bear the potential to help solve the world’s pressing problems by enabling and scaling up operations beyond human capacities. To successfully manipulate objects and perform reliable locomotion, robots require adequate models and solvers.

Traditionally, physics-based models and iterative solvers are used, and obtaining reliable solutions requires significant effort in model tuning and heuristics for good convergence.

LiftMeUp’s objective is to combine data-driven modeling with globally optimal solvers in a unique way to create an easy-to-use framework for the life-long operation of robots in challenging tasks.

The result is a transparent, sample-efficient alternative to the less interpretable and resource-hungry deep-learning solutions for robotics.

Furthermore, LiftMeUp builds on providing certifiably optimal methods with important consequences for safety and efficiency, as opposed to deep learning and local solvers, where different initializations can lead to entirely different solutions.

LiftMeUp is carried out at WILLOW, Inria Paris, known for cutting-edge control and locomotion research, and has three stages: first, combining concepts from Koopman theory, polynomial optimization, and kernel methods, lifting functions are inferred from data and integrated into globally optimal methods for state estimation and control.

Second, different models are optimally combined, leading to a modular framework that can be incrementally updated online.

Lastly, these novel algorithms are implemented on hardware to solve real-world locomotion and dexterous manipulation tasks.

This framework will have an important scientific impact by creating novel connections between global optimization and machine learning, enabling the use of principled over heuristic solvers in a broad range of applications in robotics and beyond.

It will entail energy and time savings for the economy and using sample-efficient and transparent models will democratize technology and build trust.