Uncalibrated Visual Compass from Omnidirectional Line Images with Application to Attitude MAV Estimation

International audienceThis paper presents a new algorithm based on previous results of the authors, for the estimation of the yaw angle of an omnidirectional camera robot undergoing a 6-DoF rigid motion. Our real-time algorithm is uncalibrated, robust to noisy data, and it only relies on the projection of 3-D parallel lines as image features. Numerical and real-world experiments conducted with an eye-in-hand robot manipulator, which we used to simulate the 3-D motion of a Micro unmanned Aerial Vehicle (MAV), show the accuracy and reliability of our estimation algorithm

KCT: a MATLAB toolbox for motion control of KUKA robot manipulators

Abstract—The Kuka Control Toolbox (KCT) is a collection of MATLAB functions for motion control of KUKA robot manipulators, developed to offer an intuitive and high-level programming interface to the user. The toolbox, which is compatible with all 6 DOF small and low payload KUKA robots that use the Eth.RSIXML, runs on a remote computer connected with the KUKA controller via TCP/IP. KCT includes more than 30 functions, spanning operations such as forward and inverse kinematics computation, point-to-point joint and Cartesian control, trajectory generation, graphical display and diagnostics. The flexibility, ease of use and reliability of the toolbox is demonstrated through two applicative examples. I

Cooperative human-robot haptic navigation

International audienceThis paper proposes a novel use of haptic feedback for human navigation with a mobile robot. Assuming that a path-planner has provided a mobile robot with an obstacle-free trajectory, the vehicle must steer the human from an initial to a desired target position by only interacting with him/her via a custom-designed vibro-tactile bracelet. The subject is free to decide his/her own pace and a warning vibrational signal is generated by the bracelet only when a large deviation with respect to the planned trajectory is detected by the vision sensor on-board the robot. This leads to a cooperative navigation system that is less intrusive, more flexible and easy-to-use than the ones existing in literature. The effectiveness of the proposed system is demonstrated via extensive real-world experiments

Uncalibrated Visual Compass from Omnidirectional Line Images with Application to Attitude MAV Estimation

International audienceThis paper presents a new algorithm based on previous results of the authors, for the estimation of the yaw angle of an omnidirectional camera robot undergoing a 6-DoF rigid motion. Our real-time algorithm is uncalibrated, robust to noisy data, and it only relies on the projection of 3-D parallel lines as image features. Numerical and real-world experiments conducted with an eye-in-hand robot manipulator, which we used to simulate the 3-D motion of a Micro unmanned Aerial Vehicle (MAV), show the accuracy and reliability of our estimation algorithm

Evaluation of a predictive approach in steering the human locomotion via haptic feedback

In this paper, we present a haptic guidance policy to steer the user along predefined paths, and we evaluate a predictive approach to compensate actuation delays that humans have when they are guided along a given trajectory via sensory stimuli. The proposed navigation policy exploits the nonholonomic nature of human locomotion in goal directed paths, which leads to a very simple guidance mechanism. The proposed method has been evaluated in a real scenario where seven human subjects were asked to walk along a set of predefined paths, and were guided via vibrotactile cues. Their poses as well as the related distances from the path have been recorded using an accurate optical tracking system. Results revealed that an average error of 0.24 m is achieved by using the proposed haptic policy, and that the predictive approach does not bring significant improvements to the path following problem for what concerns the distance error. On the contrary, the predictive approach achieved a definitely lower activation time of the haptic interfaces

Cooperative human-robot haptic navigation

International audienceThis paper proposes a novel use of haptic feedback for human navigation with a mobile robot. Assuming that a path-planner has provided a mobile robot with an obstacle-free trajectory, the vehicle must steer the human from an initial to a desired target position by only interacting with him/her via a custom-designed vibro-tactile bracelet. The subject is free to decide his/her own pace and a warning vibrational signal is generated by the bracelet only when a large deviation with respect to the planned trajectory is detected by the vision sensor on-board the robot. This leads to a cooperative navigation system that is less intrusive, more flexible and easy-to-use than the ones existing in literature. The effectiveness of the proposed system is demonstrated via extensive real-world experiments

Autonomous planning and control of soft untethered grippers in unstructured environments

The use of small, maneuverable, untethered and reconfigurable robots could provide numerous advantages in various micromanipulation tasks. Examples include microassembly, pick-and-place of fragile microobjects for lab-on-a-chip applications, assisted hatching for in-vitro fertilization and minimally invasive surgery. This study assesses the potential of soft untethered magnetic grippers as alternatives or complements to conventional tethered or rigid micromanipulators. We demonstrate closed-loop control of untethered grippers and automated pick-and-place of biological material on porcine tissue in an unstructured environment. We also demonstrate the ability of the soft grippers to recognize and sort non-biological micro-scale objects. The fully autonomous nature of the experiments is made possible by the integration of planning and decision-making algorithms, as well as by closed-loop temperature and electromagnetic motion control. The grippers are capable of completing pick-and-place tasks of biological material at an average velocity of 1.8±0.71 mm/s and a drop-off error of 0.62±0.22 mm. Color-sensitive sorting of three micro-scale objects is completed at a velocity of 1.21±0.68 mm/s and a drop-off error of 0.85±0.41 mm. Our findings suggest that improved autonomous un-tethered grippers could augment the capabilities of current soft-robotic instruments especially in advanced tasks involving manipulation

Design, characterization and control of thermally-responsive and magnetically-actuated micro-grippers at the air-water interface

The design and control of untethered microrobotic agents has drawn a lot of attention in recent years. This technology truly possesses the potential to revolutionize the field of minimally invasive surgery and microassembly. However, miniaturization and reliable actuation of micro-fabricated grippers are still challenging at sub-millimeter scale. In this study, we design, manufacture, characterize, and control four similarly-structured semi-rigid thermoresponsive micro-grippers. Furthermore, we develop a closed loop-control algorithm to demonstrate and compare the performance of the said grippers when moving in hard-to-reach and unpredictable environments. Finally, we analyze the grasping characteristics of three of the presented designs. Overall, not only does the study demonstrate motion control in unstructured dynamic environments-at velocities up to 3.4, 2.9, 3.3, and 1 body-lengths/s with 980, 750, 250, and 100 μm-sized grippers, respectively-but it also aims to provide quantitative data and considerations to help a targeted design of magnetically-controlled thin micro-grippers