**Aliakbar Akbari \*, Mohammed Diab and Jan Rosell**

Institute of Industrial and Control Engineering, Universitat Politècnica de Catalunya, 08034 Barcelona, Spain; mohammed.diab@upc.edu (M.D.); jan.rosell@upc.edu (J.R.)

**\*** Correspondence: ali.akbari101@gmail.com

Received: 8 February 2020; Accepted: 24 February 2020; Published: 1 March 2020

**Abstract:** Manipulation planning under incomplete information is a highly challenging task for mobile manipulators. Uncertainty can be resolved by robot perception modules or using human knowledge in the execution process. Human operators can also collaborate with robots for the execution of some difficult actions or as helpers in sharing the task knowledge. In this scope, a contingent-based task and motion planning is proposed taking into account robot uncertainty and human–robot interactions, resulting a tree-shaped set of geometrically feasible plans. Different sorts of geometric reasoning processes are embedded inside the planner to cope with task constraints like detecting occluding objects when a robot needs to grasp an object. The proposal has been evaluated with different challenging scenarios in simulation and a real environment.

**Keywords:** task and motion planning; manipulation planning; robot-human interactions; perception
