Robot co-design, where the morphology of a robot is optimized jointly with a learned policy
to solve a specific task, is an emerging area of research. It holds particular promise for soft …

Multi-cellular robot design aims to create robots comprised of numerous cells that can be
efficiently controlled to perform diverse tasks. Previous research has demonstrated the …

Soft robot design is an intricate field with unique challenges due to its complex and vast
search space. In the past literature, evolutionary computation algorithms, including novel …

We present Dynamics-Guided Diffusion Model, a data-driven framework for generating
manipulator geometry designs for a given manipulation task. Instead of training different …

Training an agent to adapt to specific tasks through co-optimization of morphology and
control has widely attracted attention. However, whether there exists an optimal …

A strict graph-matching mechanism brings normativeness to graph grammar but leads to
graph grammar insufficiency when processing fuzzy grammatical structures. To address this …

Modular reconfigurable manipulators enable quick adaptation and versatility to address
different application environments and tailor to the specific requirements of the tasks. Task …

Modular robot and multi-robot systems share a concept in common: composition, ie the
study of how parts can be combined so they can be used to achieve certain objectives. Our …

Hazardous environments such as disaster affected areas, outer space, and radiation
affected areas are dangerous for humans. Autonomous systems which can navigate through …