A framework is presented in this paper for the control of a multi-sensor robot under several constraints. In this approach, the features coming from several sensors are treated as a single feature vector. The core of our approach is a weighting matrix that balances the contribution of each feature, allowing to take constraints into account. The constraints are considered as additional features that are smoothly injected in the control law. Multi-sensor modeling is introduced for the design of the control law, drawing similarities with linear quadratic control. The main properties are exposed and we propose several strategies to cope with the main drawbacks. The framework is validated on a complex experiment, illustrating various aspects of the approach. The goal is the positioning of a 6 DOF robot arm with 3D visual servoing. The considered constraints are both eye-in-hand and eye-to-hand visibility, together with joint limits avoidance. The system is thus highly overdetermined, yet the task can be performed while ensuring several combination of constraints.

In this paper we present the mechanical and control design of a magnetic tracked mobile robot. The robot is designed to move on vertical steel ship hulls and to be able to carry 100 kg payload, including its own weight. The mechanical components are presented and the sizing of the magnetic tracks is detailed. All computation is embedded in order to reduce time delays between processes and to keep the robot functional even in case of signal loss with the ground station. The main sensor of the robot is a 2D laser scanner, that gives information on the hull surface and is used for several tasks. We focus on the welding task and expose the control algorithm that allows the robot to follow a straight line for the welding process.

-sensor data fusion in sensor-based control: application to multi-camera visual servoing. IEEE Int. Conf. on Robotics and Automation, ICRA'11, 2011, Shanghai, China, China. pp.4518-4523, 2011 Multi-sensor data fusion in sensor-based control:application to multi-camera visual servoingOlivier Kermorgant and François Chaumette Abstract-A low-level sensor fusion scheme is presented for the positioning of a multi-sensor robot. This non-hierarchical framework can be used for robot arms or other velocitycontrolled robots, and is part of the task function approach. A stability analysis is presented for the general case, then several control laws illustrate the versatility of the framework. This approach is applied to the multi-camera eye-in-hand/eyeto-hand configuration in visual servoing. Experimental results point out the feasibility and the effectiveness of the proposed control laws. Mono-camera and multi-camera schemes are compared, showing that the proposed sensor fusion scheme improves the behavior of a robot arm.

In this paper we present a dynamic simulator for intervention autonomous underwater vehicles. Prototyping and testing of such robots is often tedious and costly, and realistic simulation can greatly help validating several aspects of the project. In order to benefit from existing software, the presented system is integrated with ROS, through the Gazebo dynamic simulator, and the underwater image rendering UWSim. The whole approach allows realistic rendering of dynamic multirobot simulation, with contact physics, buoyancy, hydrodynamic damping and low-level PID control. This paper details the modeling choices that are done and exposes how to build its own AUV model. Integration with other ROS programs is exposed, and a simulation shows an example of behavior during a black box recovery mission.

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Abstract-This paper addresses the perpendicular and parallel parking problems of car-like vehicles for both forward and reverse maneuvers in one trial by extending the work presented in [1] using a multi sensor based controller with a weighted control scheme. The perception problem is discussed briefly considering a Velodyne VLP-16 and a SICK LMS151 as the sensors providing the required exteroceptive information. The results obtained from simulations and real experimentation for different parking scenarios show the validity and potential of the proposed approach. Furthermore, it is shown that, despite the need of handling several constraints for collision avoidance, the required computation time of the proposed approach is small enough to be used online.

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Formation control gains significant attention in the multi-robot system field as it contributes to a vast range of applications, such as transportation. This paper presents a constrained optimization-based control law for cooperative logistics mission, which consists of rigid shape formation control, group navigation, individual and team obstacle avoidance tasks. These tasks are defined as equality and inequality constraints with different levels of priority. Hierarchical quadratic programming (HQP) approach is used to solve for the optimal solution with an inclusion of velocity limits as inequality constraints to ensure implementation feasibility. Experiment using actual industrial robots is demonstrated in order to validate the theory.