Robotics problem: Manipulation

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Literature Review: Manipulation problem for Robotics

This “Ten Problems for Robotics in the 2020s” booklet identifies ten relevant areas from very recent contributions put forward at academic level in the form journal articles, conference proceedings and students theses. Ten freely accessible internet references have been selected for each area and direct links are provided at the end of each chapter for own consultation. Our selected references do not intend to mirror ranking indexes nor establish novel classifications. On the contrary, they are meant to represent peer-reviewed, diverse and scientifically-sound case studies for vertical dissemination aimed at non-specialist readers. They will also be able to scoop even more references through the bibliography that is reported at the end of each selected reference.

Without further ado, these are the ten problems that we are going to introduce in this booklet:

  1. self learning, 
  2. manipulation,
  3. research,
  4. motion,
  5. detection,
  6. action planning,
  7. simulation,
  8. soft,
  9. education,
  10. accountability.

Each problem has its own dedicated chapter made of an introductory section, a short presentation of the ten selected references and a conclusions section.

The final chapter of this booklet will report the conclusions from each chapter again in order to provide a complete executive summary.

2 Manipulation

THE PROBLEM — The last decade has seen substantial growth in research on the problem of robot manipulation. Manipulation tasks remain highly challenging for robotics and vision, and without benchmarks. The creation and the collection of training datasets are still difficult.

CASE STUDIES — … buy this booklet from Amazon …

CONCLUSIONS — Mastery of manipulation skills can be achieved using model-based or model-free reinforcement learning. Robust reinforcement learning policies combine behavioral cloning skills to solve composite tasks. Robotic manipulation currently lacks benchmarks that are widely accepted in fields of comparable size and importance, such as Simultaneous Localization and Mapping, and object detection in computer vision. Learning actions from human demonstration is an emerging trend for designing intelligent robotic systems, which can be referred as video to command. The largest known crowdsourced teleoperated robot manipulation dataset, consisting of over 111 hours of data across 54 users, was collected in 1 week on 3 Sawyer robot arms using the RoboTurk platform. State-of-the-art control strategies implemented on exoskeletons are mainly focused on robot joint-level position control, although accurate control of fingertip positions and forces is a requirement for reaching human-like dexterity and manipulation. To enable robots to understand shape and function of objects, a camera can be used to estimate the 6D pose of the target into. New force/tactile sensor equipping the gripper of a mobile manipulator allow robots to successfully perform manipulation tasks unfeasible with a standard fixed grasp. An important aspect of aerial manipulation is the safe and stable interaction of the aerial manipulator with the environment. Pushing is also an essential motion primitive that dramatically extends a robot’s manipulation repertoire.

TEN FREE REFERENCES FROM THE INTERNET — … buy this booklet from Amazon …

“Ten Problems for Robotics in the 2020s” booklet for Amazon Kindle, 2020; click on the cover to go to the dedicated Amazon listing page

By TenProblems

Literature Reviews for Inquisitive Minds