Papers
4
Total Citations
79
H-Index
4
About
Chuanlang Peng is an emerging researcher specializing in agricultural robotics, with a particular focus on autonomous harvesting systems, motion planning, and deep reinforcement learning for greenhouse environments. His work centers on developing intelligent robotic solutions for tomato harvesting — one of horticulture's most labor-intensive and technically demanding challenges. Peng's most impactful contribution, "Peduncle Collision-Free Grasping Based on Deep Reinforcement Learning for Tomato Harvesting Robots" (2023), has garnered 50 citations, establishing him as a notable voice in precision agricultural automation. This work addressed a critical bottleneck in robotic harvesting: safely navigating complex plant structures without damaging delicate fruit stems. Building on this foundation, his subsequent research tackled equally pressing challenges — optimizing dual-arm coordination through intermittent stop-move motion planning, integrating human dexterous skills into robotic manipulation via improved DDPG algorithms, and redesigning harvesting arm structures to improve obstacle avoidance in confined greenhouse spaces. With nearly 80 citations across just four papers published between 2023 and 2025, Peng's rapidly growing influence reflects the urgency and relevance of his research agenda. His interdisciplinary approach — bridging robotics, machine learning, and agricultural engineering — positions him as a promising contributor to the future of smart farming and automated food production.
Research Focus
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Top Papers
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