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.

Door traversal is an essential task for a mobile manipulator to achieve autonomous navigation in indoor environment. However, it remains challenging since it requires the coupled motion of the robot and door and is composed of several sub-problems such as approaching, opening, passing through, and closing the door. This paper proposes a planning framework that formulates these sub-problems as a single problem and computes a path for the mobile manipulator to navigate from the initial position, traverse through the door, and arrive at the target position. The proposed framework obtains the path of the whole-body configuration in two steps. First, the path for the pose of the mobile robot and the path for the door angle are computed by using the graph search algorithm. In graph search, an integer variable called area indicator is introduced as an element of state, which indicates where the robot is located relative to the door. Especially, the area indicator expresses a process of door traversal. In the second step, the configuration of the manipulator is computed by the Inverse Kinematics (IK) solver from the path of the mobile robot and door angle. The proposed framework has a distinct advantage over the existing methods that manually determine several parameters such as which direction to approach the door and the angle of the door required for passage. The effectiveness of the proposed framework was validated through experiments with a nonholonomic mobile manipulator.

This paper introduces a reactive self-collision avoidance algorithm for differentially driven mobile manipulators. The proposed method mainly focuses on self-collision between a manipulator and the mobile robot. We introduce the concept of a distance buffer border (DBB), which is a 3D curved surface enclosing a buffer region of the mobile robot. The region has the thickness equal to buffer distance. When the distance between the manipulator and mobile robot is less than the buffer distance, which means the manipulator lies inside the buffer region of the mobile robot, the proposed strategy is to move the mobile robot away from the manipulator in order for the manipulator to be placed outside the border of the region, the DBB. The strategy is achieved by exerting force on the mobile robot. Therefore, the manipulator can avoid self-collision with the mobile robot without modifying the predefined motion of the manipulator in a world Cartesian coordinate frame. In particular, the direction of the force is determined by considering the non-holonomic constraint of the differentially driven mobile robot. Additionally, the reachability of the manipulator is considered to arrive at a configuration in which the manipulator can be more maneuverable. In this respect, the proposed algorithm has a distinct advantage over existing avoidance methods that do not consider the non-holonomic constraint of the mobile robot and push links away from each other without considering the workspace. To realize the desired force and resulting torque, an avoidance task is constructed by converting them into the accelerations of the mobile robot. The avoidance task is smoothly inserted with a top priority into the controller based on hierarchical quadratic programming. The proposed algorithm was implemented on a differentially driven mobile robot with a 7-DOFs robotic arm and its performance was demonstrated in various experimental scenarios.