Felix Grimminger

A Versatile Stair-Climbing Robot for Search and Rescue Applications

For disaster mitigation as well as for urban search and rescue (USAR) missions, it is often necessary to place sensors or cameras into dangerous or inaccessible areas to get a better situation awareness for the rescue personnel, before they enter a possibly dangerous area. Robots are predestined to this task, but the requirements for such mobile systems are demanding. They should be quick and agile and, at the same time, be able to deal with rough terrain and even to climb stairs. The latter is always required if the rescue personnel has to get access to higher floors inside a building. A rugged, waterproof and dust-proof corpus, and, if possible, the ability to swim, are only a few of many requirements for such robots. With those requirements in mind, the hybrid legged-wheeled robot ASGUARD was developed. This robot is able to cope with stairs, very rough terrain, and is able to move fast on flat ground. We will describe a versatile adaptive controller, based only on proprioceptive data. An additional inclination feedback is used to make the controller versatile for flat ground as well as for steep slopes and stairs. An attachable float provided, the robot is able to swim, using the same locomotion approach. By using twenty compliant legs, which are mounted around four individually rotating hip-shafts, we use an abstract model of quadruped locomotion. For the control design, four independent pattern generators are used. In contrast to many other hybrid legged-wheeled robots, we use the direct proprioceptive feedback in order to modify the internal control loop, thus adapting the model of the motion pattern. For difficult terrains, like slopes and stairs, we use a phase-adaptive approach which is using directly the proprioceptive data from the legs.

Additional DOFs and sensors for bio-inspired locomotion: Towards active spine, ankle joints, and feet for a quadruped robot

In this paper, we present the design of biologically inspired structural components which should effectively improve the locomotion and mobility characteristics when applied to a robotic system. The aim is to increase the overall performance of a complex walking robot by the purposeful use of intelligent structures. In order to achieve this goal, an improved perception of the environment and the robots own condition is needed. The structures contain a variety of functions which not only can extend the already existing locomotion behaviors of robots, but also permit further relevant applications like the contemporaneous use as supporting structure and sensor system. A precise perception of the environment is realizable with a high number of various sensors which results in large amount of data. To obtain the necessary information, a hierarchical sensor concept is used. Rigid or connecting elements are extended to single subsystems, including locally preprocessed and evaluated sensor information. The description in this paper includes the single subsystems and the planned prototype which will be used to demonstrate the possibilities of these subsystems by acting collaboratively.

CESAR: A lunar crater exploration and sample return robot

Suspicion of water ice deposits in the lunar south-polar region have sparked new interest into the earths smaller companion, and robotic crater sample return missions are being considered by a number of space agencies. The difficult terrain with an inclination of over 30°, eternal darkness and temperatures of less than -173°C make this a difficult task. In this paper we present a novel, bio-inspired light-weight system design, which demonstrates a possible approach for such a mission. The robot managed to come first in the Lunar Robotic Challenge (LRC), organised by the European Space Agency (ESA) in October 2008. Using a remote operated robot, we demonstrated to climb into and out of a lunar-like crater with inclination of more than 35° on loose substrate, and performed the collection and delivery of a 100 g soil sample without the aid of external illumination.

Adaptive compliance control of a multi‐legged stair‐climbing robot based on proprioceptive data

Purpose – The purpose of this paper is to describe an innovative compliance control architecture for hybrid multi‐legged robots. The approach was verified on the hybrid legged‐wheeled robot ASGUARD, which was inspired by quadruped animals. The adaptive compliance controller allows the system to cope with a variety of stairs, very rough terrain, and is also able to move with high velocity on flat ground without changing the control parameters. Design/methodology/approach – The paper shows how this adaptivity results in a versatile controller for hybrid legged‐wheeled robots. For the locomotion control we use an adaptive model of motion pattern generators. The control approach takes into account the proprioceptive information of the torques, which are applied on the legs. The controller itself is embedded on a FPGA‐based, custom designed motor control board. An additional proprioceptive inclination feedback is used to make the same controller more robust in terms of stair‐climbing capabilities. Findings – The robot is well suited for disaster mitigation as well as for urban search and rescue missions, where it is often necessary to place sensors or cameras into dangerous or inaccessible areas to get a better situation awareness for the rescue personnel, before they enter a possibly dangerous area. A rugged, waterproof and dust‐proof corpus and the ability to swim are additional features of the robot. Originality/value – Contrary to existing approaches, a pre‐defined walking pattern for stair‐climbing was not used, but an adaptive approach based only on internal sensor information. In contrast to many other walking pattern based robots, the direct proprioceptive feedback was used in order to modify the internal control loop, thus adapting the compliance of each leg on‐line.

Proprioceptive control of a hybrid legged-wheeled robot

In this work we describe an innovative proprioceptive control architecture for our hybrid legged-wheeled robot ASGUARD. This robot is able to cope with a variety of stairs, very rough terrain, and is able to move with the speed of two body-lengths per second on flat ground. An additional proprioceptive inclination feedback is used to make the same controller more robust in terms of stair-climbing capabilities. Contrary to existing approaches, we did not use a pre-defined walking pattern for stair climbing, but an adaptive approach based only on internal sensor information. The data we use in our architecture is based on proprioceptive information, like body inclination and external torques, which are acting on the driving motors. In this work we show how this adaptivity results in a versatile controller for hybrid legged-wheeled robots. For the locomotion control we use an adaptive model of motion pattern generators. In contrast to many other walking pattern based robots, we use the direct proprioceptive feedback in order to modify the internal control loop, thus adapting the compliance of each leg on-line. For different terrains and stairs we use a phase-adaptive pattern which is using directly the proprioceptive data from each leg. We show that our adaptive controller is able to improve the stair-climbing behaviour in terms of energy consumption and energy distribution.

Concept evaluation of a new biologically inspired robot “LittleApe”

In this paper we present a concept and an evaluation of an ape-like robot which is quite similar to its biological model. Aim of our project LittleApe is to build a small and extreme lightweight robot that is capable of walking on two and four legs as well as of changing from a four-legged posture to a two-legged posture, manipulating small objects, and which is also able to climb. LittleApe is modelled with attributes of a chimpanzee regarding limb proportions, spinal column, centre of mass, walking pattern, and range of motion. The concept of LittleApe is tested in simulation while building the real system. Two aspects were chosen to evaluate the concept described in detail within this paper. The first aspect comprises the use of an evolutionary method and the comparison of different morphologies. Based on the results from the first one, the second aspect deals with the manoeuvrability of the LittleApe robot.

Intelligent Mobility: Autonomous Outdoor Robotics at the DFKI

Robotic systems for outdoor applications can play an important role in the future. Tasks like exploration, surveillance or search and rescue missions benefit greatly from increased autonomy of the available systems. Outdoor environments and their high complexity pose a special challenge for existing autonomous behaviour technologies in robots. Some of these challenges in the area of navigation, plan management and sensor integration are investigated in the Intelligent Mobility (iMoby) project at the DFKI. An introduction to the project goals and the current achievements is given. Further, an outlook towards the end of the project and beyond is provided.

Development of a Low-Pressure Fluidic Servo-Valve for Wearable Haptic Interfaces and Lightweight Robotic Systems

This document presents a low-pressure servo-valve specifically designed for haptic interfaces and lightweight robotic applications. The device is able to work with hydraulic and pneumatic fluidic sources, operating within a pressure range of (0 − 50 ·105 Pa). All sensors and electronics were integrated inside the body of the valve, reducing the need for external circuits. Positioning repeatability as well as the capability to fine modulate the hydraulic flow were measured and verified. Furthermore, the static and dynamic behavior of the valve were evaluated for different working conditions, and a non-linear model identified using a recursive Hammerstein-Wiener parameter adaptation algorithm.

A HYBRID LEGGED WHEEL CLIMBING ROBOT FOR MARINE INSPECTION

The inspection of marine vessels is currently performed manually. Inspectors use sensors (e.g. cameras, devices for non-destructive testing) to detect damaged areas, cracks, and corrosion in large cargo holds, tanks, and other parts of a ship. Due to the size and complex geometry of most ships, ship inspection is time-consuming and expensive. The EU funded project MINOAS develops concepts for a Marine Inspection Robotic Assistant System to improve and automate ship inspection. A central part of MINOAS is to evaluate the use of a cooperative fleet of robots, including areal drones, magnetic climbing robots, and underwater crawlers, for ship inspection. In this paper we describe a first concept for one component of the MINOAS robot fleet, a magnetic crawler for the inspection of large cargo holds and large tanks. We show how a lightweight system using magnetic wheels (including hybrid leg-wheels) and a passive magnetic tail can successfully climb tall metallic walls and overcome small obstacles.