Doctoral Project: Online Learning of Constrained Manipulation from Corrective and Explorative Demonstrations

Principal Investigator

Description of the research project

See below (same as doctoral project because there is only one doctoral project in this project)


Description of the doctoral project

Contact-rich manipulation tasks of articulated objects, such as the opening and closing of door latches, still pose significant challenges for the state of the art in robot manipulation. This project will extract manipulation strategies from human demonstrations through kinesthetic teaching. This project will develop an innovative approach to Learning from Demonstration that learns robust policies from few, yet diverse demonstrations. The resulting data will give rise to general manipulation strategies based on techniques from machine learning. Effectively, the acquired data acts as a prior for the (deep) learning methods employed for policy generation. The goal is to produce a means of programming a robot system by merging data and learning to produce robust, complex, and general contact-rich manipulation.

Application procedure

Applications should include: motivation letter, curriculum vitae, transcripts of records (for both BSc and MSc + doctoral degree if applicaple), copies of degree certificates (BSc, MSc), abstracts of Bachelor-, Master-thesis, e.g. doctoral thesis, list of publications and one selected manuscript (if applicable), two names of qualified persons who are willing to provide references, and any documents candidates feel may help us assess their competence.

To ensure equal opportunities between women and men, applications by women with the required qualifications are explicitly desired. Qualified individuals with disabilities will be favored. Applications are also expressly welcomed from suitably qualified persons seeking to be entered as “gender diverse” in the public register. The TU Berlin values the diversity of its members and is committed to the goals of equal opportunities.

Please send copies only. Original documents will not be returned.


  • MSc degree in com­puter sci­ence or sim­ilar field
  • Research exper­i­ence in robot­ics, machine learn­ing, com­puter vis­ion, and/or con­trol
  • Exper­i­ence in Learn­ing from Demon­stra­tion and force con­trol desir­able
  • Exper­i­ence in apply­ing (deep) learn­ing to con­trol prob­lems desir­able
  • Interest in inter­dis­cip­lin­ary research in the con­text of the Cen­ter of Excel­lence “Sci­ence of Intel­li­gence”
  • Excel­lent soft­ware engin­eer­ing and pro­gram­ming skills in C++
  • Excel­lent Eng­lish writ­ing and com­mu­nic­a­tion skills

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