Deep Neural Networks (DNNs) are vulnerable to backdoor attacks, which poison the training
set to alter the model prediction over samples with a specific trigger. While existing efforts …

Robots are notoriously difficult to design because of complex interdependencies between
their physical structure, sensory and motor layouts, and behavior. Despite this, almost every …

Modular robots can be rearranged into a new design, perhaps each day, to handle a wide
variety of tasks by forming a customized robot for each new task. However, reconfiguring just …

While significant research progress has been made in robot learning for control, unique
challenges arise when simultaneously co-optimizing morphology. Existing work has typically …

Robots have been used in all sorts of automation, and yet the design of robots remains
mainly a manual task. We seek to provide design tools to automate the design of robots …

This paper presents a novel robotic arm system, named PAPRAS (Plug-And-Play Robotic
Arm System). PAPRAS consists of a portable robotic arm (s), docking mount (s), and …

Metarobotics aims to combine next generation wireless communication, multisense
immersion, and collective intelligence to provide a pervasive, itinerant, and noninvasive …

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 …

Optimizing the morphologies and the controllers that adapt to various tasks is a critical issue
in the field of robot design, aka. embodied intelligence. Previous works typically model it as …

The advantages of modular robot systems stem from their ability to change between different
configurations, enabling them to adapt to complex and dynamic real-world environments …