Active learning is a decision-making process. In both abstract and physical settings, active
learning demands both analysis and action. This is a review of active learning in robotics …

The physical design of a robot and the policy that controls its motion are inherently coupled,
and should be determined according to the task and environment. In an increasing number …

We present parametric trajectory optimization, a method for simultaneously computing
physical parameters, actuation requirements, and robot motions for more efficient robot …

In this work, we take a step towards bridging the gap between the theory of formal synthesis
and its application to real-world, complex, robotic systems. In particular, we present an end …

Digital fabrication is changing the way we design and manufacture the objects around us.
Digital fabrication machines enable mass-customisation. However, customising the …

This paper discusses the integration challenges and strategies for designing mobile robots,
by focusing on the task-driven, optimal selection of hardware and software to balance safety …

From smart toys and household appliances to personal robots, electromechanical devices
play an increasingly important role in our daily lives. Rather than relying on gadgets that are …

The contemporary era struggles with the intricate challenge of designing “complex systems”.
These systems are characterized by intricate webs of interactions that interlace their …

This work contributes to a compositional theory of “codesign” that allows to optimally design
a robotic platform. In this framework, the user describes each subsystem as a monotone …

Modular self-assembling systems typically assume that modules are present to assemble.
But in sparsely observed ocean environments modules of an aquatic modular robotic system …