Deforestation and improper plantation of trees are the key issues in realizing sustainable environmental management. The AutoForest PlantBot, an autonomous robot system, is introduced in this paper, which makes use of advanced image processing, path optimization, and real-time navigation for efficient tree plantation. The system employs the Deep Forest Package for 92% accurate tree detection and uses Dijkstra’s algorithm to find optimal routes, cutting tree removal by 40% as compared to traditional straight-path approaches. The hardware system consists of an Arduino-controlled rover with BO motors, a GPS module, ultrasonic sensors, and an automated drill mechanism, providing accurate plantation with an accuracy of ±2 cm. The outcomes validate the system’s potential for large-scale reforestation applications. Future developments will emphasize integrating reinforcement learning for adaptive path optimization and using renewable energy sources for sustainable operation.