Robert Adams

Papers

Total Citations

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About

Robert Adams is a researcher at the intersection of artificial intelligence, environmental sustainability, and swarm robotics. His most impactful work, "Trash and Recycled Material Identification using Convolutional Neural Networks (CNN)" (2020, 35 citations), pioneers the use of deep learning for automated waste detection in public spaces. By applying image processing and CNN architectures, Adams directly addresses the challenge of municipal waste management, offering a scalable solution for smart city infrastructure. This contribution not only advances computer vision applications but also provides a practical tool for improving urban cleanliness and recycling efficiency. In parallel, Adams explores the frontiers of collective robotics. His paper "Simulating micro-robots to find a point of interest under noise and with limited communication using Particle Swarm Optimization" (2017, 9 citations) demonstrates how swarms of micro-robots can collaboratively locate targets in noisy, communication-constrained environments. By adapting Particle Swarm Optimization (PSO) for real-world constraints, he bridges theoretical swarm intelligence with practical robotic deployment. Though his citation counts are modest, Adams’ work is notable for its dual focus: applying AI to pressing environmental problems while advancing the fundamental capabilities of distributed robotic systems. His research offers a compelling vision of how intelligent systems—from neural networks to robot swarms—can be harnessed for societal benefit.