Martin Görner

Stereo-vision-based navigation of a six-legged walking robot in unknown rough terrain

In this paper we present a visual navigation algorithm for the six-legged walking robot DLR Crawler in rough terrain. The algorithm is based on stereo images from which depth images are computed using the semi-global matching (SGM) method. Further, a visual odometry is calculated along with an error measure. Pose estimates are obtained by fusing inertial data with relative leg odometry and visual odometry measurements using an indirect information filter. The visual odometry error measure is used in the filtering process to put lower weights on erroneous visual odometry data, hence, improving the robustness of pose estimation. From the estimated poses and the depth images, a dense digital terrain map is created by applying the locus method. The traversability of the terrain is estimated by a plane fitting approach and paths are planned using a D* Lite planner taking the traversability of the terrain and the current motion capabilities of the robot into account. Motion commands and the traversability measures of the upcoming terrain are sent to the walking layer of the robot so that it can choose an appropriate gait for the terrain. Experimental results show the accuracy of the navigation algorithm and its robustness against visual disturbances.

Multisensor data fusion for robust pose estimation of a six-legged walking robot

For autonomous navigation tasks it is important that the robot always has a good estimate of its current pose with respect to its starting position and - in terms of orientation - with respect to the gravity vector. For this, the robot should make use of all available information and be robust against the failure of single sensors. In this paper a multisensor data fusion algorithm for the six-legged walking robot DLR Crawler is presented. The algorithm is based on an indirect feedback information filter that fuses measurements from an inertial measurement unit (IMU) with relative 3D leg odometry measurements and relative 3D visual odometry measurements from a stereo camera. Errors of the visual odometry are computed and considered in the filtering process in order to achieve accurate pose estimates which are robust against visual odometry failure. The algorithm was successfully tested and results are presented.

The DLR Crawler: evaluation of gaits and control of an actively compliant six‐legged walking robot

Purpose – The purpose of this paper is to present and evaluate methods of control and gait generation for the DLR Crawler – a six‐legged walking robot prototype based on the fingers of the DLR Hand II.Design/methodology/approach – Following the institutes philosophy, the DLR Crawler is a highly integrated mechatronic device. As in all DLR robots, joint torque sensing plays an important role to allow actively compliant interaction with the environment. To control the Crawler a joint compliance controller is implemented and two different methods of gait generation are in use. The first method, intended for moderately uneven terrain, employs scalable patterns of fixed coordination combined with a leg extension reflex. For the second method, used in rougher terrain, a set of rules found by biologists in stick insect studies is applied. Based on these rules gaits emerge according to a velocity command. These gaits are combined with several reflexes to a reactive walking algorithm.Findings – The compliance cont...

The DLR-Crawler: A testbed for actively compliant hexapod walking based on the fingers of DLR-Hand II

Walking is a fascinating way of locomotion that is very robust, especially in unstructured terrain. Many researchers devote their time to understanding its underlying principles and to build robots based on their findings. Using the fingers of DLR-Hand II a six-legged actively compliant walking robot is developed. It is intended to be used as testbed for the evaluation of different force- and position-based leg and gait control algorithms for hexapod walking in rough terrain. Following a brief overview of the finger hardware, the use of fingers as legs is analyzed and discussed. The body geometry as well as the systems constituting the robot are described. The compliance control algorithm used is explained and finally some experimental results are presented.

A modally adaptive control for multi-contact cyclic motions in compliantly actuated robotic systems

Compliant actuators in robotic systems improve robustness against rigid impacts and increase the performance and efficiency of periodic motions such as hitting, jumping and running. However, in the case of rigid impacts, as they can occur during hitting or running, the system behavior is changed compared to free motions which turns the control into a challenging task. We introduce a controller that excites periodic motions along the direction of an intrinsic mechanical oscillation mode. The controller requires no model knowledge and adapts to a modal excitation by means of measurement of the states. We experimentally show that the controller is able to stabilize a hitting motion on the variable stiffness robot DLR Hand Arm System. Further, we demonstrate by simulation that the approach applies for legged robotic systems with compliantly actuated joints. The controlled system can approach different modes of motion such as jumping, hopping and running, and thereby, it is able to handle the repeated occurrence of robot-ground contacts.

A leg proprioception based 6 DOF odometry for statically stable walking robots

This article presents a 3D odometry algorithm for statically stable walking robots that only uses proprioceptive data delivered by joint angle and joint torque sensors embedded within the legs. The algorithm intrinsically handles each kind of emerging statically stable gait and is independent of predefined gait patterns. Additionally, the algorithm can be equally applied to stiff robots as well as to robots with compliant joints. Based on the proprioceptive information a 6 degrees of freedom (DOF) pose estimate is calculated in three steps. First, point clouds, represented by the foot positions with respect to the body frame at two consecutive time steps, are matched and provide a 6 DOF estimate for the relative body motion. The obtained relative motion estimates are summed up over time giving a 6 DOF pose estimate with respect to the start frame. Second, joint torque measurement based pitch and roll angle estimates are determined. Finally in a third step, these estimates are used to stabilize the orientation angles calculated in the first step by data fusion employing an error state Kalman filter. The algorithm is implemented and tested on the DLR Crawler, an actively compliant six-legged walking robot. For this specific robot, experimental data is provided and the performance is evaluated in flat terrain and on gravel, at different joint stiffness settings and for various emerging gaits. Based on this data, problems associated with the odometry of statically stable walking robots are identified and discussed. Further, some results for crossing slopes and edges in a complete 3D scenario are presented.

Analysis and evaluation of the stability of a biologically inspired, Leg loss tolerant gait for six- and eight-legged walking robots

This article analyzes and evaluates the stability of the biologically inspired gait of the DLR Crawler, a walking hexapod robot, with respect to leg loss. Using a kinematic simulation, ranges of velocity commands that result in stable gait coordination are determined for both cases, the undamaged robot and the robot experiencing the loss of a single leg. The results give insight how to adjust the motion commands after the loss of a leg. Further, a simplified dynamic simulation is used to analyze the effect of leg loss on the walking stability. Heuristic measures like curvature and length of the traveled path, roll and pitch angles are employed to evaluate the walking stability and performance. Some methods like shifting the COG or stiffening the variably compliant joints are proposed and discussed with respect to their ability to improve the walking performance in case of leg loss. In the end, the presented concepts are extended and for the first time applied to a simulated eight-legged robot.

THE DLR-CRAWLER: GAITS AND CONTROL OF AN ACTIVELY COMPLIANT HEXAPOD

This paper presents the control and gait generation for the DLR-Crawler, nan actively compliant hexapod based on the fingers of DLR-Hand II. The first ngait generation method combines a fixed pattern with a leg extension reflex nand an obstacle avoidance reflex. The second method employs leg coordina- ntion based on Cruse’s rules and some reflexes to master uneven terrain. Both nmethods show smooth walking on even ground as well as on gravel.