My Ph.D. thesis title is "Knowledge representation and reasoning for Perception-based manipulation planning", which deals with different types of robotic manipulation problems such as table-top and navigation.  During his Ph.D., he developed:

1.  A framework called, PMK - Perception and Manipulation Knowledge, which modeled under standardized foundations, Suggested Upper Merged Ontology (SUMO), and Core Ontology for Robotics and Automation(CORA). Also, some reasoning predicates which facilitate the manipulation planning process that involve the integration of symbolic and geometric levels of planning.

2. A framework called, FailRecOnt - An ontology-based approach for failure interpretation and recovery in automated planning and execution, which increases the capabilities of the robot to interpret failures and provide recovery strategies. 

3. A framework called, SkillMaN - A Skill-based Robotic Manipulation Framework based on Perception and Reasoning, which uses a multi-model sensory system contains Camera and Radio Frequency Identification (RFID). Moreover, Reasoning, which uses learning-based techniques of adaptation m to increase the use of experiential knowledge in the planning system.

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Some of these frameworks were a part of joint works during my visits to other labs. The visited labs are IAI (Institute for Artificial Intelligence), Bremen, Germany, and Third Institute of Physics Biophysics, Georg-August University Göttingen.

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The aforementioned works have been tested in simulation, and also with practical examples in real environments. The robots used are YuMi, TIAGo-PAL.