The design and control of autonomous systems that operate in uncertain or adversarial
environments can be facilitated by formal modeling and analysis. Probabilistic model …

Neuromorphic hardware implements biological neurons and synapses to execute a spiking
neural network (SNN)-based machine learning. We present SpiNeMap, a design …

We consider the problem of accurate and high-rate self-localization for a mobile robot. We
adaptively combine the speed information acquired by proprioceptive sensors with …

We propose a methodology for enforcing a set of coordination rules onto a multi-robot
system, based on the use of Petri nets to model the team of robots, safe linear temporal logic …

Although the field of distributed optimization is well developed, relevant literature focused on
the application of distributed optimization to multi-robot problems is limited. This survey …

The daily working hours of mobile robots are limited primarily by battery life. Most systems
use a combination of thresholds and fixed periods to decide when to charge. This produces …

We consider the problem of co-designing embodied intelligence as a whole in a structured
way, from hardware components such as propulsion systems and sensors to software …

Future advances in deep learning and its impact on the development of artificial intelligence
(AI) in all fields depend heavily on data size and computational power. Sacrificing massive …

This paper presents a methodology for synthesizing a motion plan for a mobile robot to
ensure that the robot never gets depleted with battery charge while carrying out its mission …

Facilitated by the emergence of neuromorphic hardware, neuromorphic algorithms mimic
the brain's asynchronous computation to improve energy efficiency, low latency, and …