Forestry of tomorrow
Envisioning how harvester operators can feel in control and make the best decisions in a semi-automated world.
Designing the user interface for operating future, highly automated forestry machines for year 2020.
Focusing on the aspect of "Operating the Harvester Crane".
duration & team
8 weeks. Ezgi Sabir, Trieuvy Luu, Lars Sundelin.
According to forestry industry, we are moving towards highly automated and smart forestry machines. Currently the automation is seen in few parts of the operation but in the future, we are expected to see more. The higher automation doesn’t guarantee better efficiency as the work relies heavily on the skills of the operator.
The aim of this project was to design the interface for the semi-autonomous Harvester machine in 2020 for beginner operators. Our idea was to take the needs of operators through extensive user research and combine them with the vision of highly automated forestry machines of tomorrow. Our group’s approach was to not see the interface as a screen unit but rather as a balance of tactile controls and visual information.
Our proposal is built on three interaction levels: an augmented GUI that gives the operator an overview on his tasks, a futuristic controller that invites the operator to initiate automated actions and a haptic behavior that makes the operator to feel in control of the operation by giving him a clear understanding of the machine’s state.
The new interface design shows the enhanced future work state of the operators by lowering their mental workload. It also significantly cuts down the learning time which takes years for beginner operators.
This project was part of the “Professional Users” course and has been done in collaboration with SLU and Skogtekniska Klustret.
" BEFORE MAKING SELF-SUSTAINING SMART FORESTRY MACHINES,
WE MUST DESIGN SEMI-AUTONOMOUS SYSTEMS
WHERE HUMANS AND TECHNOLOGY WORK TOGETHER. "
DANIEL ORTÍZ MORALES, phd in Umeå university
We visited the forest to interview and observe both Harvester & Forwarder operators on their regular work day. The aim was to find out the operators’ mental model and how operation is being conducted in today. We also visited the school of forestry and interviewed young operators. We showed them cards where the main aspects of the operation such as the UI elements, various feedbacks were written on it and asked them to put in their importance order.
We also read relevant literature papers on forestry, automation and robotics. This allowed us to make spot-on technology assumptions for year 2020.
After analyzing our research material, we created three groups to categorize our insights which are Learn, Enhance and Focus.
LEARN >> The most difficult to learn for them is to coordinate left and right joysticks simultaneously which is called “the flow”. Being good at “flow” demands several years of training. This is due to the bad semantics of the joysticks and buttons as the actions and the controller elements aren’t directly mapped.
ENHANCE >> We noticed that operators were disconnected from their own actions. Harvester machine is an unique environment with cabin constantly in motion and environment is dynamic. The current joysticks and buttons don’t give any feedback to operators. Interface doesn’t give any confirmation and communicate the work progress very little with the operators.
FOCUS >> Operators currently have a heavy mental workload on a typical day while cutting hundreds of trees. They have to execute their current task and plan the next step at the same time. This is an exhausting work after a whole day in the forest. Automation, as the newest advancement in Harvester machine, isn’t really improving their work state.
Defining the focus areas helped us to start the ideation phase. We have performed two ideation sessions: first one was done internally as a team and second one was together with other students from the Master programmes, learning from their experience with heavy machinery design.
Making assumptions on the state of forestry for 2030 gave us a clear view for 2020, our target year. By having these, we were able to create scenarios which we further continue with prototyping and testing.
In order to design a multimodal interaction, we applied various prototyping methods. Through bodystorming, we acted out each interaction in the user flow as an operator by making simple props and including our prototypes. By doing several bodystorming sessions, we were able to map the user journey, the system actions and experience the balance of multiple interface elements from operators’ point of view. Throughout the project we created many prototypes at different stages in order to reflect on the experience. These prototypes varied from low paper mockups prototypes to more complex ones.
It gives the operator an overview on his tasks. Augmentation benefits the operator as it makes the task easier by showing relevant information and informing the operator on the automated actions.
The new controller is able to invite the operator to initiate automated actions. Operators can make their own decisions and either accept the automation or operate manually. The new controller doesn’t show the complete set of functions for all times, instead, it shows the needed functions for that step of the process.
When the system offers an automated action, operator feels a nudge in his hand on the joystick. This empowers the operators to feel in control by giving them a clear understanding of the machine’s state.