This paper addresses two intertwined needs for collaborative robots operating in shop-floor environments. The first is the ability to perform complex manipulation operations, such as those on articulated or even flexible objects, in a way robust to a high degree of variability in the actions possibly carried out by human operators during collaborative tasks. The second is encoding in such operations a basic knowledge about physical laws (e.g., gravity), and their effects on the models used by the robot to plan its actions, to generate more robust plans. We adopt the manipulation in three-dimensional space of articulated objects as an effective use case to ground both needs, and we use a variant of the Planning Domain Definition Language to integrate the planning process with a notion of gravity. Different complexity levels in modelling gravity are evaluated, which tradeoff model faithfulness and performance. A thorough validation of the framework is done in simulation using a dual-arm Baxter manipulator.
|Title of host publication||The 32th International Conference on Tools with Artificial Intelligence (ICTAI) 2020|
|Publication status||Accepted/In press - 2 Sep 2020|
|Event||32nd International Conference on Tools with Artificial Intelligence - Online due to COVID-19|
Duration: 9 Nov 2020 → 11 Nov 2020
Conference number: 32
|Conference||32nd International Conference on Tools with Artificial Intelligence|
|Abbreviated title||ICTAI 2020|
|Period||9/11/20 → 11/11/20|
Bertolucci, R., Capitanelli, A., Maratea, M., Mastrogiovanni, F., & Vallati, M. (Accepted/In press). Collaborative Robotic Manipulation: A Use Case of Articulated Objects in Three-dimensions with Gravity. In The 32th International Conference on Tools with Artificial Intelligence (ICTAI) 2020 IEEE.