On obstacle-cluttered construction sites where heavy equipment is in use, safety and productivity issues are major concerns. Efficient and effective algorithms for obstacle avoidance and path planning, based on real-time three dimensional spatial modeling, have the potential not only to obviate collisions between heavy equipment and other on-site objects, but also to allow autonomous heavy equipment to move to target positions quickly without any accidents. Therefore, algorithms for obstacle avoidance and path planning can play a key role in addressing safety and productivity issues. This research constitutes a preliminary study of a path planning method. Several algorithms for image data acquisition, real-time 3D spatial modeling, and shortest path finding were adapted and developed. These algorithms were integrated to construct an entire, comprehensive collision-free path. Once the path planning algorithm was developed, computer simulation was conducted to verify its accuracy. The algorithm worked well in a proposed simulation environment cluttered with a static object and a moving object. The occupancy grid algorithm successfully built a suitable 3D local model in real-time, and the path finding algorithm was able to produce a collision-free motion trajectory. This research result shows that the proposed path planning approach is potentially feasible for contributing to improved safety and productivity, and to future applications for autonomous heavy equipment operation in construction