This image shows the forces recorded while opening four mechanisms. The pictures on the top highlight a key mechanical element of each mechanism. Bottom plots show forces tangential to the motion of the handle as a function of the device's configuration. Lighter green indicates trials with higher average velocity. Left: Refrigerator. High initial force due to low pressure interior. Middle Left: Springloaded door. Large forces throughout movement due to linkage at top. Middle Right: Kitchen cabinet. Non-linear spring keeps it closed with max force at about 4 deg. Right: Toolchest drawer. Larger force halfway due to 2nd stage of telescoping rail.
Instrumental activities of daily living (IADLs) involve physical interactions with diverse mechanical systems found within human environments. In this paper, we describe our efforts to capture the everyday mechanics of doors and drawers, which form an important sub-class of mechanical systems for IADLs. We also discuss the implications of our results for the design of assistive robots. By answering questions such as "How high are the handles of most doors and drawers?" and "What forces are necessary to open most doors and drawers?", our approach can inform robot designers as they make tradeoffs between competing requirements for assistive robots, such as cost, workspace, and power.
Using a custom motion/force capture system, we captured kinematic trajectories and forces while operating 29 doors and 15 drawers in 6 homes and 1 office building in Atlanta, GA, USA. We also hand-measured the kinematics of 299 doors and 152 drawers in 11 area homes. We show that operation of these seemingly simple mechanisms involves significant complexities, including non-linear forces and large kinematic variation. We also show that the data exhibit significant structure. For example, 91.8% of the variation in the force sequences used to open doors can be represented using a 2-dimensional linear subspace. This complexity and structure suggests that capturing everyday mechanics may be a useful approach for improving the design of assistive robots.
The Python code associated with this project can be
Our hardware design is available at: