R. Dillmann

LAURON V: A versatile six-legged walking robot with advanced maneuverability

Adaptive multi-legged walking robots are predestined to be applied in rough and hazardous terrain. Their walking and climbing skills allow them to operate at places that are unreachable for most wheeled vehicles. In this paper, we present the design and development of the new six-legged walking robot LAURON V with its improved kinematics and robust mechanical structure. Each leg has four independent joints that enable LAURON to cope with steep inclines, large obstacles and makes it possible to manipulate objects with its front legs. Autonomy, robustness and a large payload capacity together with its impressive terrain adaptability make LAURONV highly suitable for all kinds of field applications.

Unified GPU voxel collision detection for mobile manipulation planning

This paper gives an overview on our framework for efficient collision detection in robotic applications. It unifies different data structures and algorithms that are optimized for Graphics Processing Unit (GPU) architectures. A speed-up in various planning scenarios is achieved by utilizing storage structures that meet specific demands of typical use-cases like mobile platform planning or full body planning. The system is also able to monitor the execution of motion trajectories for intruding dynamic obstacles and triggers a replanning or stops the execution. The presented collision detection is deployed in local dynamic planning with live pointcloud data as well as in global a-priori planning. Three different mobile manipulation scenarios are used to evaluate the performance of our approach.

Reactive posture behaviors for stable legged locomotion over steep inclines and large obstacles

Multi-legged walking robots often make use of sophisticated control architectures to play their strengths in rough and unknown environments. The adaptability of these robots is an essential skill to achieve the maneuverability and autonomy needed in their application fields. In this work we present a reactive control approach for the hexapod LAURONV, which enables it to overcome large obstacles and steep slopes without any knowledge about the environment. A key to this success can also be seen in the increased kinematic adaptability due to the fourth rotational joint in the bio-inspired leg kinematics. An extended experimental evaluation shows that the reactive posture behaviors are able to create an effective and efficient locomotion in challenging environments.

KAIRO 3: A modular reconfigurable robot for search and rescue field missions

Search and rescue field missions, especially in environments which are dangerous for humans, increasingly requires the usage of robust and flexible robots. We describe the development of the modular reconfigurable robot KAIRO 3 focusing on applications in search and rescue, inspection and maintenance. After a short retrospect of previous generations of modular robots, the latest design of KAIRO 3 is presented. In particular, enhancements of the mechatronics and the control software are shown. Furthermore, the necessity to increase the flexibility of search and rescue robots will be demonstrated. To comply with this requirement, we utilized reconfiguration and adaptation of modular robots. Finally, the field results of applying KAIRO 3 at a civil protection field exercise are discussed.

KAIRO 3: Moving over stairs & unknown obstacles with reconfigurable snake-like robots

We present a planning approach for complex motions of reconfigurable snake-like robots to overcome challenging obstacles like stairs or large steps. The current robot configuration as well as different optimization criteria like distance, time or energy, are taken into account. The planning time remains unaffected by the amount of robot modules by combining the planning method with a follow-the-leader control approach. Implementation details on the developed method are presented and extensively evaluated with the reconfigurable snake-like inspection robot KAIRO 3 in three different scenarios. Our results show that the approach enables snake-like robots to overcome previously unknown obstacles according to their robot configuration.

Development and calibration of KaRoLa, a compact, high-resolution 3D laser scanner

We present KaRoLa, a new rotating 3D laser scanner with a modular and flexible hardware design and an integrated control software stack implemented in the ROS framework. Based on our requirements - light-weight and compact hardware, high resolution and accuracy - we compare different 2D laser range finders which are commercially available. We describe the hardware design, including the mechanical and electrical components, and the included software stack in detail. Furthermore, we present a particle swarm based calibration method to compensate mounting offsets between the 2D laser scanner and the rotational axis. The calibration significantly improves the overall accuracy and lowers the requirements for the mounting precision. Field studies for evaluating KaRoLa in real-world application scenarios such as planetary exploration and search and rescue missions complete this article.

Evaluation of physics engines for robotic simulations with a special focus on the dynamics of walking robots

Detailed simulations of robotic systems, including their components and dynamics, play an increasingly important role in the development of new robotic systems and their applications. There are many physics engines with a mature development stage, but all of them suffer from fundamental inaccuracies due to the approximative character of the internal calculations. This article provides an in-detail evaluation of the physics engines Bullet, ODE and PhysX with a focus on robotics and legged locomotion. We present a variety of run-time experiments which provide an insight into these engines, their strengths and weaknesses. Our findings offer valuable information for the application-specific selection of a physics engine for robotics simulations.

Hardware and software architecture of a bimanual mobile manipulator for industrial application

We present our recent work on the Soft- and Hardware-design of a bi-manual mobile manipulation platform that can be used to evaluate planing paradigms in different scenarios, especially for industrial applications. The integration of different hardware parts (platform, arms, hands, head) establishes a testbed for diverse software packages, especially our fast and flexible multilevel planning framework. The architecture of our system covers all levels of sense and control and enables the robot to carry out a wide range of tasks important for adaptive industrial production systems. To maximize usability in future factories, our robot can be programmed in an intuitive process with very little expert knowledge.

Fault diagnosis and system status monitoring for a six-legged walking robot

Rough, unstructured and hazardous areas are typical application scenarios for autonomous mobile robots. In the case of an error or fault, these robots cannot rely on a human to recover or repair them. Therefore, intelligent fault detection systems have to be developed that can autonomously detect faults and create a system status corresponding to the operability of the robot. After a fault has been detected, it might be possible to adapt the robot and still continue with its primary task. This paper presents a fault diagnosis and status monitoring system for a six-legged walking robot. Our developed system is based on expert knowledge and was implemented on the six-legged robot LAURON. It is able to detect seven different types of faults and errors, ranging from mechanical coupling problems to the total loss of leg controller units. The status monitoring part gives the operator a detailed, but still understandable status report about the most important components and their functionality.

Robust 3D scan segmentation for teleoperation tasks in areas contaminated by radiation

3D data collected by a laser scanner has great potential for robotic applications. Exact geometrical models of the environment surrounding the robot can be created from these point clouds. But, before creating any model, the 3D point cloud has to be segmented and depending on the size and quality of the point cloud, this can be a very challenging task. This article describes a robust 3D scan segmentation technique, which is capable of segmenting a 3D point cloud in a short amount of time. The results of the segmentation are used to assist a teleoperator to manoeuvre a robot through an unknown environment. Our segmentation approach copes with indoor and outdoor environments, using only a minimum of assumptions, which makes it very robust. A 3D visualisation illustrates the segmentation results in a clear and user-friendly way.