Human-Robot Coordination in Agile Robot Manipulation

With the practical demands in flexible and adaptive robot manipulation skills in various environment settings, there are more challenges to be tackled to enable the robot with valid responsive behaviors in task handling. This paper discuss on the methods to achieve agile robot manipulations tasks with the advantages from human-robot teleoperation, robot perception, knowledge-based robot programming, robot motion planning and robot skill learning. Teleoperation serves as a typical Human-Robot Interaction (HRI) manner to allow the human user to guide the robot behavior in a direct manner. Robot automation, including the sensor perception (object detection, pose estimation etc.), motion planning and motion control that can handle well defined problems, but is also lack of general sense of understanding capability and not good at solving not fully defined task challenges. An agile robotic system should have a knowledge database which defines the skill sets required for the robot to handle various robot tasks. Meanwhile, the system should be able to take human assistance inputs through HRI when the robot is stuck. Moreover, the system should be able to pick up new skill set with each human knowledge input. Methodology discussion is the main scope of the paper, and preliminary experiments on telemanipulation with UR5 robot are demonstrated to show the flexible robot guidance through HRI inputs. Future work will aim to add in perception, motion planning, and picking up skill modules to come up with a more agile solution in handling variation of tasks.