4,398 research outputs found
Analysis and Observations from the First Amazon Picking Challenge
This paper presents a overview of the inaugural Amazon Picking Challenge
along with a summary of a survey conducted among the 26 participating teams.
The challenge goal was to design an autonomous robot to pick items from a
warehouse shelf. This task is currently performed by human workers, and there
is hope that robots can someday help increase efficiency and throughput while
lowering cost. We report on a 28-question survey posed to the teams to learn
about each team's background, mechanism design, perception apparatus, planning
and control approach. We identify trends in this data, correlate it with each
team's success in the competition, and discuss observations and lessons learned
based on survey results and the authors' personal experiences during the
challenge
Autonomous vision-guided bi-manual grasping and manipulation
This paper describes the implementation, demonstration and evaluation of a variety of autonomous, vision-guided manipulation capabilities, using a dual-arm Baxter robot. Initially, symmetric coordinated bi-manual manipulation based on kinematic tracking algorithm was implemented on the robot to enable a master-slave manipulation system. We demonstrate the efficacy of this approach with a human-robot collaboration experiment, where a human operator moves the master arm along arbitrary trajectories and the slave arm automatically follows the master arm while maintaining a constant relative pose between the two end-effectors. Next, this concept was extended to perform dual-arm manipulation without human intervention. To this extent, an image-based visual servoing scheme has been developed to control the motion of arms for positioning them at a desired grasp locations. Next we combine this with a dynamic position controller to move the grasped object using both arms in a prescribed trajectory. The presented approach has been validated by performing numerous symmetric and asymmetric bi-manual manipulations at different conditions. Our experiments demonstrated 80% success rate in performing the symmetric dual-arm manipulation tasks; and 73% success rate in performing asymmetric dualarm manipulation tasks
Hybrid position/force control of two cooperative flexible manipulators working in 3D space
科研費報告書収録論文(課題番号:07455416・基盤研究(B)(2)・H7~H9/研究代表者:内山, 勝/フレキシブル双腕ロボットの協調制御に関する研究
Dynamic Active Constraints for Surgical Robots using Vector Field Inequalities
Robotic assistance allows surgeons to perform dexterous and tremor-free
procedures, but robotic aid is still underrepresented in procedures with
constrained workspaces, such as deep brain neurosurgery and endonasal surgery.
In these procedures, surgeons have restricted vision to areas near the surgical
tooltips, which increases the risk of unexpected collisions between the shafts
of the instruments and their surroundings. In this work, our
vector-field-inequalities method is extended to provide dynamic
active-constraints to any number of robots and moving objects sharing the same
workspace. The method is evaluated with experiments and simulations in which
robot tools have to avoid collisions autonomously and in real-time, in a
constrained endonasal surgical environment. Simulations show that with our
method the combined trajectory error of two robotic systems is optimal.
Experiments using a real robotic system show that the method can autonomously
prevent collisions between the moving robots themselves and between the robots
and the environment. Moreover, the framework is also successfully verified
under teleoperation with tool-tissue interactions.Comment: Accepted on T-RO 2019, 19 Page
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