Workshop on “Task-based Optimal Design of Robots“, co-located with the 2014 IEEE International Conference on Robotics and Automation (ICRA 2014), Hong Kong, China, May 31 – June 7, 2014
- Deadline for submission: March 14, 2014
- Notification of acceptance: March 22, 2014
- Submission of camera ready version: April 7, 2014
- Workshop date: May 31, 2014
Real-world robot tasks, to be executed in unstructured and highly dynamic environments, often require the optimization of some component of the whole robot architecture in order to maximize a given measure of performance (e.g., related to computational or energetic parameters). This is even more important when task-dependent functional requirements (e.g., related to safety or other operating conditions) must be guaranteed.
This Workshop aims at bridging two important, partly overlapping and constantly evolving fields of research, namely optimal robot design and task-based design of robots. The former features a wide adoption of optimization and search techniques in order to design robot parts, especially for what concerns their dimensioning, according to a number of optimality criteria. The latter, also known as task-oriented robot design, deals with a wider set of goals, including the choice between different kinds of mechanical designs and control architectures, the selection of the proper number of degrees of freedom as well as the kind of joints to be used, the adoption of a suitable locomotion system and part shape, just to name but few.
Task-based design often precedes optimization. Although formal methods exist to determine the most appropriate type of mechanism for the task at hand, these are seldom applied to robot design and, in most cases, critical choices are based more on the experience of the designer and on empirical considerations rather than on a formal analysis of requirements and constraints. However, when considered as distinct design phases, we argue that a sequential approach cannot lead but to a suboptimal design.
The main objective of this Workshop is to foster the current debate in the application of optimization and search techniques to task-based robot design, in order to learn and spread good practices across the Robotics research community. The Workshop will try to address the following questions:
- What are the most relevant robot design problems to address in the upcoming few years?
- What are promising modelling methods to formalize such problems?
- Are there good practices to formalize a robot design problem as a well known optimisation problem?
- Are the existing performance measures suitable or is there a need for the introduction of new ones?
- Are there prototypical problems which robot design problems can be reduced to?
- Is it possible to identify benchmarking test cases?
- How to ensure and validate the consistency of the models from the early stages of the design process?
The objective of the Workshop is to elicit and share best practices in order to (1) create a research community working on this topic (2) by means of well-defined case studies and benchmarking scenarios (3) in order to lead to a possible industry-oriented exploitation of results. We wish to:
- introduce the use of optimization techniques from the initial phases of robot design
- keep modelling overhead under control
- shorten the time-to-market required to deploy real-world robot systems
- identify categories of problems in task-based robot design
- assess key steps toward the development of new mathematical and software tools
- identify and overcome common obstacles, as far as conceptual (e.g., unclear or undefined requirements), economical (e.g., a prototype is due in a short time) and cultural (e.g., knowledge gap between designers and mathematicians) aspects are concerned
- identify novel ways of applying optimization techniques to task based robot design
- promote an industry-oriented exploitation of results.
Field experiences and success stories are particularly welcome.
- Aude Billard (Ecole Polytechnique Federale de Lausanne, Switzerland)
- Stephane Caro (CNRS/IRCCyN, France)
- Howie Choset (Carnegie Mellon University, USA)
- Nak Young Chong (Japan Advanced Institute of Science and Technology, Japan)
- Feng Gao (Shanghai Jiao Tong University, China)
- Qiaode Jeffrey Ge (Stony Brook University, USA)
- Venkat N. Krovi (University at Buffalo, USA)
- Xinjun Liu (Tsinghua University, China)
- Katja Mombaur (Ruprecht-Karls-Universitat Heidelberg, Germany)
- Francesco Nori (Istituto Italiano di Tecnologia, Italy)
- Emanuel Todorov (University of Washington, USA)
- Dan Zhang (Ontario Institute of Technology, Canada)
The topics are related (but not limited) to:
- optimal robot design
- task-based design of robots
- optimization and search models
- algorithms for robot design
- benchmarking and use case scenarios
- optimization-based design of robot mechanisms
- software tools
- market needs
Researchers presenting their results at the Workshop will be requested to submit a 4-page extended abstract, including figures, tables and references.
PDF files formatted in conformance with the ICRA 2014 manuscript guidelines available at:
must be sent to Cristiano Nattero at:
We ask the contributors to dedicate a specific (mandatory) section of the abstract to suggest answers to the questions posed in the Abstract above and (optionally) to introduce new ones. The extended abstracts will form the Workshop Proceedings. We are evaluating a post-Workshop extended publication of results.
- Cristiano Nattero. Department of Informatics, Bioengineering, Robotics and Systems Engineering, University of Genoa, Italy.
- Wei-Zhong Guo. Institute of Design and Control Engineering for Heavy Equipment, School of Mechanical Engineering, Shanghai Jiao Tong University, China.
- Fulvio Mastrogiovanni. Department of Informatics, Bioengineering, Robotics and Systems Engineering, University of Genoa, Italy.
For any inquiry please send an e-mail to the Organizers at:
- cristiano DOT nattero AT unige DOT it
- wzguo AT sjtu DOT edu DOT cn
- fulvio DOT mastrogiovanni AT unige DOT it
The Call for Paper can be downloaded from here