Mobile robot and manipulator have a long history on their development. Combining these two robots, mobile manipulator has the potential of versatile skills. It has a high dimensional state space. However, combining these two robots causes many problems. First of all, the control system becomes complicated. Most manipulators actuate with the assumption that their basement is fixed. On the other hand, the mobile base and the manipulator give dynamic effects to each other. Therefore, we should consider the effects when we control the robot. Secondly, the target control accuracy would be lower than a fixed manipulator. As containing high dimensional state space, it inevitably leads to uncertainty (especially in mobile part).
To handle these problems, we are focusing on controlling and planning this mobile manipulator.
The robot consists of two robots. The mobile base is Clearpath Husky and the manipulator is Franka Emika Panda
It has a powerful computation unit to solve complicated whole-body dynamics and plan motions in high dimensional state space. The specification is described below.
- CPU: Intel i7-7700K
- RAM: 16 GB
- Storage (SSD): 500 GB
- OS: Ubuntu 16.04 (with preempt_rt kernel)
- Whole-body control framework
- Hierarchical Quadratic Programming (HQP) based control
- Motion and path planning
- Manipulator motion planning with contact
- Path planning of non-holonomic mobile base
Research in this project
Continuous Task Transition Approach for Robot Controller based on Hierarchical Quadratic Programming
The robots with high Degrees of Freedom (DoF) such as humanoids and mobile manipulators are expected to perform multiple tasks simultaneously. Hierarchical Quadratic Programming (HQP) can effectively compute a solution for strictly prioritized tasks. However, the continuity of control input is not guaranteed when the priorities of the tasks are modified during operation. This paper proposes a continuous task transition method for HQP based controller to insert, remove, and swap arbitrary tasks without discontinuity. Smooth task transition is assured because our approach uses activation parameters of the new and existing tasks without modifying control structure. The proposed approach is applied to various task transition scenarios including joint limit, singularity, and obstacle avoidance to guarantee the stable execution of the robot. The proposed control scheme was implemented on a 7-DoF robotic arm, and its performance was demonstrated by the continuity of control input during various task transition scenarios.
Source Code: Source code is available at http://github.com/ggory15/HQP_DualArmMobile
for nonholonomic mobile manipulator (Mobile Branch)
for 7dof manipulator (fixed based Branch)
Experiments with a real robot (mobile base: Clearpath Husky, manipulator: Franka Panda)