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Found 10 papers, 3 papers with code
In-Rack Test Tube Pose Estimation Using RGB-D Data
Accurate robotic manipulation of test tubes in biology and medical industries is becoming increasingly important to address workforce shortages and improve worker safety.
Automatically Prepare Training Data for YOLO Using Robotic In-Hand Observation and Synthesis
The collected and synthetic images are combined to train a deep detection neural network.
Accelerating Robot Learning of Contact-Rich Manipulations: A Curriculum Learning Study
The Reinforcement Learning (RL) paradigm has been an essential tool for automating robotic tasks.
Variable Compliance Control for Robotic Peg-in-Hole Assembly: A Deep Reinforcement Learning Approach
Industrial robot manipulators are playing a more significant role in modern manufacturing industries.
Functionally Divided Manipulation Synergy for Controlling Multi-fingered Hands
Synergy supplies a practical approach for expressing various postures of a multi-fingered hand.
Robotics
Selecting and Designing Grippers for an Assembly Task in a Structured Approach
In this paper, we present a structured approach of selecting and designing a set of grippers for an assembly task.
Robotics
Team O2AS at the World Robot Summit 2018: An Approach to Robotic Kitting and Assembly Tasks using General Purpose Grippers and Tools
We propose a versatile robotic system for kitting and assembly tasks which uses no jigs or commercial tool changers.
Learning Force Control for Contact-rich Manipulation Tasks with Rigid Position-controlled Robots
Thirdly, we developed a fail-safe mechanism for safely training an RL agent on manipulation tasks using a real rigid robot manipulator.
Planning an Efficient and Robust Base Sequence for a Mobile Manipulator Performing Multiple Pick-and-place Tasks
In this paper, we address efficiently and robustly collecting objects stored in different trays using a mobile manipulator.
Robotics
Motion Planning through Demonstration to Deal with Complex Motions in Assembly Process
Complex and skillful motions in actual assembly process are challenging for the robot to generate with existing motion planning approaches, because some key poses during the human assembly can be too skillful for the robot to realize automatically.
