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IROS 2020 | Multi-mode Trajectory Optimization for Impact-aware Manipulation

  • 2020.10.28
  • News
IROS 2020 | AIRS — 9 papers with 2 award finalists

We are going to introduce these papers during the time of IROS 2020. Below is the article Multi-mode Trajectory Optimization for Impact-aware Manipulation, the corresponding author of this paper is Professor Sethu Vijayakumar. Professor Sethu Vijayakumar directs one of our International Collaboration Joint Project titled [Mobile Collaborative Robots: Addressing Real World Challenges] setup between the University of Edinburgh and AIRS, with Professor Tin Lun Lam. 

Research Background

Safe and robust robot manipulation under switching dynamics still poses many challenges. Typically, manipulation tasks require making and breaking contact with objects. This results in challenges in motion planning and control due to, among other factors, (i) the hybrid nature of the problem and (ii) the uncertainties that arises due to contact dynamics. As a typical example scenario, consider an agent that attempts to stop an object in motion, as shown in the following figure. In such a case, the agent needs to address the following challenges: 1) Plan discontinuous motions through contact, 2) Control the robot’s compliance to mitigate impact.

Abstract

The transition from free motion to contact is a challenging problem in robotics, in part due to its hybrid nature. Additionally, disregarding the effects of impacts at the motion planning level often results in intractable impulsive contact forces. In this paper, we introduce an impact-aware multi-mode trajectory optimization (TO) method that combines hybrid dynamics and hybrid control in a coherent fashion.

A key concept is the incorporation of an explicit contact force transmission model in the TO method. This allows the simultaneous optimization of the contact forces, contact timings, continuous motion trajectories and compliance, while satisfying task constraints. We compare our method against standard compliance control and an impact-agnostic TO method in physical simulations. Further, we experimentally validate the proposed method with a robot manipulator on the task of halting a large-momentum object.

Authors

Lei Yan is the co-first author of this paper, who is the post doc of UoE in UK and he is the strand leader of “Multi-Agent Collaborative Manipulation” of the international joint research project between AIRS and UoE. His major is Robotics, and the research field is multi-mode trajectory optimization and control, decentralized multi-robot collaboration.

The corresponding author of this paper is Professor Sethu Vijayakumar. Professor Vijayakumar is Professor of Robotics at the University of Edinburgh and an Adjunct Faculty of the University of Southern California, Los Angeles, the Co-Programme Director of the Alan Turing Institute and a visiting Research Scientist at the ATR Computational Neuroscience Labs, Kyoto-Japan. His research interest spans a broad interdisciplinary curriculum involving basic research in the fields of robotics, statistical machine learning, motor control, planning and optimization in autonomous systems and computational neuroscience. He is a fellow of the Royal Society of Edinburgh.

Professor Sethu Vijayakumar directs one of our International Collaboration Joint Project titled [Mobile Collaborative Robots: Addressing Real World Challenges] setup between the University of Edinburgh and AIRS, with Professor Tin Lun Lam. Professor Lam is faculty at CUHK-SZ and is the director of Research Center on Intelligent Robots of AIRS. The project aims to make fundamental and applied advances in the field of artificial intelligence and robotics, with current research focus in  the areas of perception, motion planning and control in the field of high dimensional robotics system and HRI.

Acknowledgement

This work is supported by the Honda Research Institute Europe, the EPSRC CDT in Robotics and Autonomous Systems (EP/L016834/1), EPSRC UK RAI Hub in Future AI and Robotics for Space (FAIR-SPACE: EP/R026092/1), UKIndia Education and Research Initiative (UKIERI DST 2016-17-0152), and Shenzhen Institute of Artificial Intelligence and Robotics for Society (2019-ICP002). The authors would like to thank Henrique Ferrolho for his help with the video.

Related readings:

Multi-mode Trajectory Optimization for Impact-aware Manipulation

International Joint Research Project(AIRS-UoE)

International Collaborations