Steerable wheeled mobile robots are able to perform arbitrary three-dimensional (3-D) planar trajectories, only after initializing the steer joint vector to the proper values. These robots employ fully steerable conventional wheels. Hence, they have higher load carrying capacity than their holonomic counterparts, and as such are preferable for industrial applications. Industrial setups nowadays are being prepared for the emerging field of human-robot collaboration/cooperation. Such field is highly dynamic, due to fast moving human workers, sharing the operation space. This imposes the need for human safe trajectory generators that can lead to frequent halts in motion, replanning, and to sudden, discontinuous changes in the position of the robot's instantaneous center of rotation (ICR). Indeed, this requires steer joint reconfiguration to the newly computed trajectory. This issue is almost ignored in the literature and motivates this work. The authors propose a new ICR-based kinematic controller, that is capable of handling discontinuity in commanded velocity while respecting the maximum joint performance limit. This is done by formulating a quadratic optimization problem with linear constraints in the 2-D ICR space. The controller is also robust against representation and kinematic singularities. It has been tested successfully on the Neobotix-MPO700 industrial mobile robot.

Non-holonomic omnidirectional mobile robots have higher load carrying capacity than their holonomic counterparts. Once the steer joint configuration is initialized, they can perform arbitrarily complex three-dimensional trajectories in the plane of motion and, as such, are more suitable for industrial contexts. However, their kinematic model presents representational and structural singularities, solutions to which must respect actuator performance limits. Recent research efforts have provided either simple restricting of the velocity space (among which few considered hardware limits) or complex non-restricting (no hardware limits considered) solutions. Most of these efforts are providing solutions at the kinematic control level. Instead, here we propose both a representational singularity free kinematic model, and a simple numeric treatment for the kinematic singularity. We further provide a method to tune the latter, to respect the actuator acceleration limits. Thanks to its steer rate damping behavior, the method can be further extended, to respect joint limits. Another benefit is the treatment of the singularity at the level of the kinematic model, which enhances real time capabilities. The developed method has been tested successfully on the Neobotix-MPO700 mobile robot and shown superior results as compared to the embedded controller.

In this paper, we address the problem of long travel mobile manipulation for steerable wheeled mobile robots (SWMR) operating in human shared environment. On one hand, a small footprint is required while maintaining a fixed arm configuration, to make robot motion predictable for near individuals during the long traverse. On the other hand, redundancy resolution poses a challenge since there is no direct kinematic mapping between the task and joint spaces for SWMR. Hence, we propose a redundancy resolution algorithm that enables switching between 3 modes of operation based on the Euclidean norm of the motion task error. In particular, we employ a floating base model for the mobile platform, and enhance the end effector motion performance by predicting the error between such model and the actual (SWMR) one. Such error is then compensated using the highly responsive arm manipulator. The proposed methodology is successfully validated in simulations on a Neobotix-MPO700 SWMR with a Kuka LWR-IV manipulator mounted on it.