Articulated robot

About: Articulated robot is a research topic. Over the lifetime, 4364 publications have been published within this topic receiving 52442 citations.

Development of an Adaptive Mobile Robot for In-Pipe Inspection Task

Abstract: For the purpose of performing internal inspection task of pipe, a robot based on adaptive mobile mechanism is developed. The robot equipped with one actuator has two working modes, a normal working mode and an assistant working mode. Robot under normal working mode performs monitoring tasks and travels in the pipe, while under assistant enhanced mode robot will surmount obstacle without any other driving actuator during executing tasks. The special feature is achieved by applying the adaptive mobile mechanism we proposed in this paper. A prototype has been set up and experiments have been conducted to testify the adaptability and efficiency of the robot. The results show that the robot can successfully climb up a step that is formed by concentric junction with a height of 5 mm.

Teleoperation control of Baxter robot using body motion tracking

Abstract: In this paper, we use Kinect Xbox 360 sensor to implement the motion control of Baxter robot, a semi humanoid robot with limbs of 7 DOF joints with collision avoidance capabilities. Two different methods using vector approach and inverse kinematics approach have been designed to achieve a given task. Primitive experiments have been carried out to verify the effectiveness of the developed methods. Human motions is captured by Kinect sensor and calculated with Processing Software using SimpleOpenNI wrapper for OpenNI and NITE. UDP protocol is adopted to send reference motion to Baxter robot. Python and RosPy script programming kit is used to calculate joint angles of Baxter robot based on vector approach and inverse kinematics approach. The experimental results demonstrate that both of our proposed approaches have achieved satisfactory performance.

Controlling articulated robots in task-space with spiking silicon neurons

Abstract: Emulating how humans coordinate articulated limbs within the brain's power budget promises to accelerate progress in building autonomous biomimetic robots. Here, we used a neuromorphic approach — low-power analog silicon spiking neurons — to control an articulated robot in real-time. We obtained a closed-form control function that computes robot motor torques given the robot's joint angles (state) and desired end-effector forces; factorized the function into a set of sub-functions over five unique three-dimensional domains; and regressed each sub-function on to the steady-state spiking responses of one out of five silicon spiking-neuron pools. The spiking pools controlled a three degree-of-freedom robot's motor torques in real-time and performed reaches to arbitrary locations in space with less than 2 cm root-mean-square trajectory tracking error (of an analytical controller). The controller is compliant and can draw shapes with a pen on a dynamically perturbed surface while remaining stable. Using force control resulted in linear responses to perturbations in end-effector coordinates (task-space), which effectively filtered noise due to neuron spikes. Factorizing the controller reduced the neural regression's complexity to cubic in the dynamic range of the robot's state and desired forces. Doing so made acquiring spiking responses for regression tractable in time (∼2–3 min), and enabled reliable trajectory tracking with only 1280 neurons. This is the first time a neuromorphic system has achieved realtime manipulation for an articulated robot with three or more degrees-of-freedom.

Motion planning for all-terrain vehicles: a physical modeling approach for coping with dynamic and contact interaction constraints

Abstract: Addresses modeling and global motion planning issues for an autonomous wheeled mobile robot moving on an uneven three-dimensional terrain. We focus particularly on the issue of dealing with dynamic and wheel/ground interaction constraints. A key feature of our approach is that it incorporates appropriate physical models to cope with the task dynamics in the motion planning paradigm. The planner is based on a two-level scheme. The high level considers a simplified two-dimensional instance of the motion task and searches a subset of the configuration space of the robot in order to generate nominal subgoals through which the robot is steered. The local level solves for continuous feasible trajectories and actuator controls to move the robot between neighboring subgoals in the presence of the entire task constraints. To the best of our knowledge, this is the first implemented planner that solves for feasible trajectories to be performed by a wheeled vehicle on quite complex terrains. Simulation results are presented for the case of a six-wheeled articulated robot.

Horizontal articulated robot

Abstract: A horizontal articulated robot has a plurality of horizontal arms coupled by joint shafts, and a working shaft disposed at the extreme end of an extreme end arm among the horizontal arms has mounting portions of an end effector formed to both the upper and lower ends thereof. With this arrangement, there can be provided a horizontal articulated robot that can cope with various work transport forms and various types of works by one type of a robot by selectively using the upper and lower sides of a working shaft.