REEM-C is able to walk stably at a speed of up to 2.5 km/h, and can even climb stairs or sit on a chair. Provided with a large autonomy, it is the right biped robot to bring your research in robotics and Artificial Intelligence one step ahead.
REEM-C is provided with 68 DoF that enable a wide set of movements inspired by the human motions. The humanoid robot’s F/T sensors, IMU, and RGB-D camera can help you smoothly implement and test your algorithms for the biped robot platform.
REEM-C is provided with 68 DoF that enable a wide set of movements inspired by the human motions. The humanoid’s F/T sensors, IMU, and RGB-D camera can help you smoothly implement and test your algorithms for your biped robot.
REEM-C robot comes with a set of skills that work right out of the box, such as walking, grasping, Whole-Body Control or Text To Speech. The humanoid biped robot platform is fully ROS based, allowing to access its sensors and actuators from ros_control real time framework or visualize them in rviz.
REEM-C biped robot using an application based on Whole Body Control (WBC). The humanoid robot developed by PAL Robotics as a robot research platform reacts to the force applied on its wrist, moving all its body in order to maintain the balance. Demonstration for exploitation of check SMCs. The EU-H2020 Project SocSMCs is supported by the European Commission. More information available on the page of the socSMCs Project.
From a user point of view the Whole Body Control (WBC) software package enables easy and safe commanding of the end effectors of the bipedal robot by just specifying where you want it to be in real world coordinates.
The Whole Body Control software package is a quadratic hierarchical solver working at 200 Hz implemented by PAL Robotics providing on-line inverse kinematics of the whole humanoid robot. The solver is given a stack of tasks with different priorities. An example of stack of task is the following one:
In this example, the Whole Body Controller is able to bring the end-effector to any desired pose in the cartesian space and to keep the gaze of the robot towards a desired point (this could be the user defined tasks) and the solutions to accomplish these lower priority tasks would always avoid joints limits and prevent self-collisions (these higher priority tasks would be included for safety).
Note that standard inverse kinematics solvers are not able to deal with joint limit and self-collisions avoidance, which are of key importance when commanding the robot.
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