Adaptive motion planning for autonomous mass excavation

Autonomous excavation has attracted interest because of the potential for increased productivity and lower labor costs. This research concerns automating a hydraulic excavator for the task of mass excavation, where tons of earth are, excavated and loaded into trucks. Fast operational speed of these machines is desired because it directly translates to higher productivity. This research focuses on the motion planning aspect of the mass excavation task, with the goal equalling the performance of a highly skilled human operator. There are several problem characteristics that led to the motion planning approach. The excavator's motions are highly repetitive and deliberate, almost to the point of being scripted. However, the precise dig, dump, and truck locations do change between passes. The hydraulic actuation system of the excavator is highly non-linear, making it difficult to model. The operation proceeds quickly, with many buckets being loaded in a short amount of time. We have developed a motion planning approach known as parameterized scripting. A script describes a task as a series of simple steps. The parameters of the script define both the specific goals for each script step, and the transitions between steps. Script parameter values are computed based on the current task conditions. The parameter values affect both the operational speed and the accuracy in achieving desired task goals. The script parameter values are computed using information about the excavator's own performance, which is gathered on-line during task execution. The excavator's performance is evaluated and stored in a data base. Memory-based learning techniques are used to find the best set of parameter values for the given task conditions. The motion planning system has resulted in autonomous performance that approaches a skilled operator in the short term and outperforms him in the long term. The autonomous excavator's motions are also more accurate and consistent than a human's. The motion planning approach provides a highly flexible system. Because the motion planner uses data gathered on-line, it can be used on any excavator in any worksite conditions. The excavator can modify its behavior to achieve maximum productivity in its current working environment.