  Addressing the challenge of roadside litter in the United States, which has
traditionally relied on costly and ineffective manual cleanup methods, this
paper presents an autonomous multi-robot system for highway litter monitoring
and collection. Our solution integrates an aerial vehicle to scan and gather
data across highway stretches with a terrestrial robot equipped with a
Convolutional Neural Network (CNN) for litter detection and mapping. Upon
detecting litter, the ground robot navigates to each pinpointed location,
re-assesses the vicinity, and employs a "greedy pickup" approach to address
potential mapping inaccuracies or litter misplacements. Through simulation
studies and real-world robotic trials, this work highlights the potential of
our proposed system for highway cleanliness and management in the context of
Robotics, Automation, and Artificial Intelligence
