Selective tasks such as harvesting or spraying of single crops are a promising research topic in agricultural automation. Inspired by industrial production, an obvious approach is to use robot manipulators in greenhouses and orchards. To exploit the potential of redundant manipulators in particular, advanced motion planning algorithms are needed. While harvesting, a new trajectory for every fruit has to be planned. Although the scenario is similar for every fruit, it is unique for each harvesting sequence. In this paper we present an efficient online planning approach which takes advantage of a simplified environment model. However, the generated trajectory is not optimal in general w.r.t. joint velocities or might even be unfeasible. Thus, we introduce an optional global offline optimization scheme which is able to find optimal trajectories in a few seconds and takes advantage of the heuristic planning as initial guess. We apply the proposed scheme to a 9-DOF agricultural manipulator for sweet-pepper harvesting and evaluate our method by extensive tests with fruit positions based on real measurements.

The exploitation of new fields of application in addition to traditional industrial production for robot manipulators (e.g. agriculture, human areas) requires extensions to the sensor as well as to the planning capabilities. Motion planning solely based on visual information performs poorly in cluttered environments since contacts with obstacles might be inevitable and thus a distinction between hard and soft objects has to be made. In our contribution we present a novel intrinsic tactile sensing module mounted on a multipurpose 9 DOF agricultural manipulator. With its innovative sensor arrangement we consider it to be a low-cost, easily manageable and efficient solution with a reasonable abstraction layer in comparison to complex torque sensing or tactile skins. The sensor provides information about the resulting force and torque. In the second part of our paper, the tactile information is used for minimizing contact forces while pursuing the end-effector tasks as long as reasonable. Hence, we present robust and efficient extensions to Resolved Motion Rate Control for real-time application. We introduce a general formulation providing control inputs in task-space, joint-space and nullspace. Thus, we design a suitable controller by feedback linearization and feed-forward terms. Results from real-world experiments show the potential of our approach. A discussion of the different control schemes completes the paper.

The drive mechanism of many robot joints are composed of an electrical actuator and a gear transmission. Besides actuator dynamics and gear elasticity, friction effects are of particular importance for accurate dynamic modeling. This paper presents the design and development of a modular testbed for experimental friction identification in modular robot drives. We have used this testbed to investigate modules that were developed at our institute for the humanoid robot Lola and an agricultural manipulator. We discovered that a friction law, similar to a law proposed in the literature, can be very accurately fitted to our measurements.

Determining the optimal solution for the inverse kinematics of redundant robots has been the focus of much previous research. Instantaneous approaches are computationally efficient, but may cause high joint velocities due to their local character. In this paper, we present an efficient implementation of a global approach following Pontryagin's Minimum Principle for online calculation. Within a moving horizon, we exploit the decoupled structure of the resulting optimal control problem by using the conjugate gradient method for solving the nonlinear dynamic problem. Different examples of cost functionals are presented and the real-time capability is shown by applying this approach to a 9-DOF redundant manipulator.

In this paper we describe an event-based walking control system for biped robots. Classically, the control of biped robots has been separated into walking pattern generation and stabilizing control. While this is an effective strategy in well-known environments, walking in rough, unmodelled terrain can easily destabilize the system. Findings from neurobiology suggest that gait generation in animals and humans is strongly linked to sensory signals indicating certain events in the gait cycle. We therefore propose an event-based controller that triggers phase transitions based on the sensed walking state instead of only relying on time-based reference trajectories. We have implemented the proposed approach on our humanoid robot Lola. We present simulations and experimental results demonstrating the effectiveness of the approach when walking over unknown obstacles.

To simplify the development of new trajectories for a humanoid robot with many joints, the ability to check for potential collisions is crucial. More importantly, to enable on line generation of general motions, such as whole-body-motion, collision avoidance must be employed, which is usually more challenging. In this paper, a model-based and efficient on-line distance calculation between links of the robot is proposed. To avoid collisions the results are projected into the null space term of the inverse-kinematics which is based on the redundancy resolution framework of LIEGEOIS. Additionally, a novel method to reduce the vertical angular momentum for a walking biped robot which uses the arm motion is proposed. It reduces the vertical angular momentum of the walking robot especially for larger steps. Since the method also works in the null-space, it can easily be combined with the proposed collision avoidance scheme. Finally, results for the proposed methods from simulations and experiments with the robot Lola are shown.

Despite many recent developments in virtual reality, an effective locomotion interface which allows for normal walking through large virtual environments was until recently still lacking. Here, we describe the new CyberWalk omnidirectional treadmill system, which makes it possible for users to walk endlessly in any direction, while never leaving the confines of the limited walking surface. The treadmill system improves on previous designs, both in its mechanical features and in the control system employed to keep users close to the center of the treadmill. As a result, users are able to start walking, vary their walking speed and direction, and stop walking as they would on a normal, stationary surface. The treadmill system was validated in two experiments, in which both the walking behavior and the performance in a basic spatial updating task were compared to that during normal overground walking. The results suggest that walking on the CyberWalk treadmill is very close to normal walking, especially after some initial familiarization. Moreover, we did not find a detrimental effect of treadmill walking in the spatial updating task. The CyberWalk system constitutes a significant step forward to bringing the real world into the laboratory or workplace.

The collaborative research center SFB453 (www.sfb453.de) aims to realize high-fidelity telepresence and teleaction systems. Telepresence and teleaction systems extend the human workspace to remote locations in order to overcome barriers like distance, scaling, danger or the human skin. Using a human-system interface the human operator controls a remotely located teleoperator. Multi-modal feedback in form of visual, auditory, and haptic data is used to increase the feeling of telepresence. Different application areas including minimally invasive surgery, on-orbit servicing, microassembly as well as tele-manufacturing and tele-maintenance are targeted.

Information about a user and his intentions can be gained evaluating images acquired from the user's subjective perspective. A possibility to yield high quality images, even under dynamic conditions, is to align a camera with the human gaze direction. Thus, the camera orientation system must cope with the high dynamic human eye movements. Since the system is intended to be head-mounted it must keep small and light. In this paper a spherical parallel manipulator with three degrees-of-freedom is introduced. Beside the kinematic the dynamic model is derived. Furthermore the workspace/package ratio is optimized. To estimate the needed actuator forces and velocities, kinematic and dynamic simulations are carried out. Simulations and measurements obtained with a prototype are presented. Both, simulations and measurements, demonstrate that the device meets the requirements.

This paper presents our new 25-DoF humanoid walking robot LOLA. The goal of our research is to realize a fast, human-like walking motion (target speed: 5 km/h). Furthermore, we want to increase the robot's autonomous, vision-guided walking capabilities. The robot has 25 degrees of freedom, including 7-DoF legs with actively driven toe joints. It is characterized by its lightweight construction, a modular, multi-sensory joint design with brushless motors and an electronics architecture using decentralized joint controllers. Special emphasis was put on an improved mass distribution of the leg apparatus to achieve good dynamic performance. The sensor system comprises absolute angular sensors in all links, two custom-made force/torque sensors in the feet and a high-precision inertial sensor in the upper body. Trajectory generation and control system aim at faster, more flexible, and more robust walking patterns.

This paper describes a real-time walking control system developed for the biped robots JOHNNIE and LOLA. Walking trajectories are planned on-line using a simplified robot model and modified by a stabilizing controller. The controller uses hybrid position/force control in task space based on a resolved motion rate scheme. Inertial stabilization is achieved by modifying the contact force trajectories. The paper includes an analysis of the dynamics of controlled bipeds, which is the basis for the proposed control system. The system was tested both in forward dynamics simulations and in experiments with JOHNNIE.

Telesurgery systems integrate multimodal communication and robotic technologies to enable surgical procedures to be performed from remote locations. They allow human surgeons to intuitively control laparoscopic instruments and to navigate within the human body. In this paper, we present selected topics on multimodal interaction in the context of telesurgery applications. These are results from the collaborative research project SFB 453 on ldquoHigh-Fidelity Telepresence and Teleactionrdquo which is funded by the German Research Foundation in the larger Munich area. The focus in this paper is on multimodal information processing and communication including simulation of surgical targets in the human body. Furthermore, we present an overview of our advanced multimodal telesurgery demonstrators that provide a comprehensive platform for our collaborative telepresence research.

Visual perception is thought to provide us with the illusion of a stable visual world that is seamless in time and space while it is continuously explored with saccades. The oculomotor system ensures retinal image stabilization during head, object, and surround motion. Prior to manipulation, objects are fixated with topdown driven look-ahead saccades, and similarly, the locomotion path is visually inspected about two steps ahead. In human-human interaction tasks gaze is not only crucial for motor intention recognition but it is also essential in detecting the direction of social attention. A new prototype of a camera motion control unit was developed that provides a sufficiently short latency and a light-weight setup for both a wearable gaze-controlled and a humanoid stereo camera system. The camera system will serve as a binocular eye plant for a humanoid active vision system. The long-term aim is to integrate eye tracking capabilities into the vision system that will equip the humanoid with the ability to infer the target of gaze of a human in human-machine cooperation scenarios. The eye tracking technology has been improved by extending it into the direction of a calibration-free operation. The antropomorphic camera motion control system was integrated into the humanoid JOHNNIE. Thereby, a new experimental tool was created that will help to evaluate the relevance of gaze and look-ahead fixations in the interaction of humans with humanoids in social contexts or during (humanoid) locomotion.

The first proof of concept of an eye movement driven head camera system was recently presented. This innovative device utilized voluntary and reflexive eye movements, which were registered by video-oculography and computed online, as signals to drive servo motors which then aligned the camera along the user's gaze direction. However, with just two degrees of freedom, this camera motion device could not compensate for roll motions around the optical axis of the system. Therefore a new three-degree-of-freedom camera motion device that is able to reproduce the whole range of possible eye movements has now been implemented. In doing so, it allows a freely mobile user to aim the optical axis of the head mounted camera system at the target(s) in the visual field at which he/she is looking, while the ocular reflexes minimize image shaking by naturally counter-rolling the "gaze in space" of the camera during head and visual scene movements as well as during locomotion. A camera guided in this way mimics the natural exploration of a visual scene and acquires video sequences from the perspective of a mobile user, while the oculomotor reflexes naturally stabilize the camera on target during head and target movements. Various documentation and teaching applications in health care, industry, and research are conceivable. This work presents the implementation of the new camera motion device and its, integration into a head camera setup including the eye tracking device.

Dynamics simulation is a valuable tool for biped robot hardware and controller design. Due to the complexity of biped walking robots, simulation times can be quite high. It is therefore important to identify the key components in modeling the system so that the phenomena of interest can be correctly predicted at a reasonable numerical cost. In this paper a detailed and a reduced simulation of the biped robot JOHNNIE are presented and results are compared with experimental data. The comparison shows that results for both models correctly predict global dynamics of the system, while some phenomena are only captured by the more complex model

The paper presents the performance enhanced humanoid robot LOLA which is currently being manufactured. The goal of the project is the realization of a fast, human-like walking motion. The robot is characterized by its lightweight construction, a modular, multi-sensory joint design with brushless motors and an electronics architecture using decentralized joint controllers. The fusion of motor, gear and sensors into a highly integrated, mechatronic joint module has several advantages for the whole system, including high power density, good dynamic performance and reliability. Additional degrees of freedom are introduced in elbow, waist and toes. Linear actuators are employed for the knee joints for a better mass distribution in the legs

The biped robot "Johnnie" is designed to achieve a dynamically stable gait pattern, allowing for high walking velocities. Besides accurate and fast sensors, a powerful computer system is essential for the performance and stability of the machine. The control system requires hard real-time capabilities and low cycle times. With our new control concept and the new computer system, walking speeds of 2.4 km/h have been achieved in experiments.