Publications

Hybrid locomotion robots—systems combining multiple modes of motion—are well-suited for challenging terrain and have broad practical applications. However, developing effective control strategies remains challenging due to nonlinear dynamics, multimodal locomotion, computational constraints, and multiple objectives. Existing solutions are often not portable to unconventional morphologies, requiring substantial redesign. This thesis proposes multiple control solutions for three morphologically distinct robots: Asguard, SherpaTT, and ARTER.

The employment of walking excavator robots, endowed with hybrid locomotion capabilities, holds considerable promise in facilitating the execution of intricate tasks in challenging terrain environments. A critical skill for such a system pertains to traversing obstacles through stepping locomotion, a process entailing the momentary disengagement of the end-effectors from the ground. Existing solutions are encumbered by two significant limitations.

The decontamination of legacy nuclear or other hazardous waste sites is a critical task that exposes human workers to significant risks. This paper presents a robotic system designed to mitigate human exposure by enabling remote, operator-supervised soil sampling using a retrofitted industrial walking excavator.

This contribution presents the development and field testing in a variety of space analogue environments of different Rimless Wheel (RW) Micro Rovers. Originally designed for search and rescue and surveillance applications, the Asguard rover demonstrated remarkable mobility capabilities, including stair climbing, water traversal, and high-speed locomotion over rough terrain.

In the field of construction and demolition waste disposal, as well as commercial waste, large-sized waste are generated that need to be sorted for high-quality recycling. In the R&D project SmartRecycling-UP, the control of hydraulic cranes and excavators was automated using AI.

Biologically Inspired Series-Parallel Hybrid Robots: Design, Analysis and Control provides an extensive review of the state-of-the-art in series-parallel hybrid robots, covering all aspects of their mechatronic system design, modelling, and control.

Biologically Inspired Series-Parallel Hybrid Robots: Design, Analysis and Control provides an extensive review of the state-of-the-art in series-parallel hybrid robots, covering all aspects of their mechatronic system design, modelling, and control.

In the SmartRecycling project, a consortium of seven partners from industry and academia develop a solution for the automated sorting of bulky wastes. If successful, this solution is expected to increase the quality and efficiency of the sorting process and to lead to a higher recycling rate in this sector.

The Autonomous Rough Terrain Excavator Robot (ARTER) is a retrofitted walking excavator developed for remote and autonomous operations in environments hostile to humans. This work highlights the key developments related to this robot: system design, terrain adaption controller, and high-level process controller.

In diesem Beitrag wird das Zukunftsthema Digitalisierung im Bereich der Altlastensanierung hinsichtlich des autonomen Einsatzes schwerer Arbeitsmaschinen in kontaminierten Bereichen beleuchtet.

Automation of heavy-duty vehicles using technologies developed in the robotics domain is gaining popularity. One such vehicle is the walking excavator with active suspension chassis for adapting to uneven terrain. The terrain adaption controller automates the suspension control by considering the factors stability, underlying terrain structure, wheel-ground distance, chassis-ground distance, etc. This work builds the controller, which actuates the joints that control the height of the wheels. Deep reinforcement learning is used, considering the complexity of the problem and transferability to other robots.

In autonomous driving, the trajectory follower is one of the critical controllers which should be capable of handling different driving scenarios. Most of the existing controllers are limited to a particular driving scenario and for a specific vehicle model. In this work, the trajectory follower is formulated as a nonlinear model predictive control problem and solved using the multiple-shooting trajectory optimization method, Gauss-Newton Multiple Shooting.

This article presents the electro-mechanical design, the control approach and the results of a field test campaign with the hybrid wheeled-leg rover SherpaTT. The rover ranges in the 150 kg class and features an actively articulated suspension system comprising four legs with actively driven and steered wheels at each leg's end.

This paper presents the control strategies used to adapt the actively articulated suspension system of the rover SherpaTT to irregular terrain. Experimental validation of the approach with the physical system is conducted and presented. The coordinated control of the legs constituting the suspension system is encapsulated in a Ground Adaption Process (GAP) that operates independently from high level motion commands.

This paper subsumes the first experiences with the hardware of the robotic system SherpaTT. The mobile platform consists of four legs, each equipped with a wheel at its end. All legs are connected via a central body. The chosen control design and approach are validated with experiments using the robotic hardware.

The presentation shows the initial results from the Ground Adaption Process (GAP) for the planetary rover SherpaTT with active suspension. The GAP process makes use of the sensory outputs from force-torque sensors attached to each wheel and the Inertial Measurement Unit.

This paper presents the lessons learned from the design and control of the exploration rover Sherpa. The mechanical design of the rover as well as its locomotion control are addressed. Achievements and drawbacks from the initial design of Sherpa are outlined and lead to a discussion of the revised design of the active suspension.

The estimation of robot's motion at the prediction step of any localization framework is commonly performed using a motion model in conjunction with inertial measurements. In the context of field robotics, articulated mobile robots have complex chassis. They might require a complete model in comparison with the traditionally used planar assumption. In this paper, we use a Jacobian motion model-based approach for real-time inertial-aided odometry.

We present an autonomous path following controller for mobile robots. Controller designs using the kinematic model of the robot is discussed for both differential and car-like steering. The kinematic model of the robot is transformed to chained form, from which the controller is developed.

Light-weight robot design have a certain degree of flexibility, which in turn introduces unwanted vibrations. This talk introduces different methods of vibration attenuation, combining feed-forward and feedback techniques. Feed-forward compensation based on Input Shaping and feedback control based on Strain gauges and Inertial Measurement Unit are used.

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.

Hybrid Leg-Wheel Robots have gained increasing popularity over the last years, as they can combine the terrain negotiation ability of legged systems with the efficiency and simplicity of wheeled systems. In this paper, the effects of locomotion patterns on the system's efficiency are studied for the legged-wheel robot Asguard.