Marko Bjelonic

• Doctor of Engineering
• PhD Student at ETH Zurich

Autonomous wheeled-legged robots have the potential to transform logistics systems, improving operational efficiency and adaptability in urban environments. Navigating urban environments, however, poses unique challenges for robots, necessitating innovative solutions for locomotion and navigation. These challenges include the need for adaptive loco...

Coordinated navigation of an arbitrary number of robots to an arbitrary number of goals is a big challenge in robotics, often hindered by scalability limitations of existing strategies. This paper introduces a decentralized multi-agent control system using neural network policies trained in simulation. By leveraging permutation invariant neural net...

Logistics and service operations involving parcel preparation, delivery, and unpacking from a supply point to a user’s home could be carried out completely by robots in the near future, taking advantage of the capabilities of the different robot morphologies for the logistics, outdoor, and domestic environments. The use of robots for parcel deliver...

The control problem of wheeled-legged locomotion is still an open problem in the robotics community. Each leg has multiple discrete control modes (rolling, point-foot mode, swing phase), which results in highly nonlinear system dynamics. Most existing works rely on model-based control approaches, and they reduce the complexity of the problem by int...

The community in legged robotics focuses on bio-inspired robots, although there are some human inventions that nature could not recreate. One of the most significant examples is the wheel which has made our transportation system more efficient and faster. Inspired by this human-made evolution, we present a survey of wheeled-legged robots, allowing...

A robotic platform for mobile manipulation needs to satisfy two contradicting requirements for many real-world applications: A compact base is required to navigate through cluttered indoor environments, while the support needs to be large enough to prevent tumbling or tip over, especially during fast manipulation operations with heavy payloads or f...

The common approach for local navigation on challenging environments with legged robots requires path planning, path following and locomotion, which usually requires a locomotion control policy that accurately tracks a commanded velocity. However, by breaking down the navigation problem into these sub-tasks, we limit the robot's capabilities since...

Navigating off-road with a fast autonomous vehicle depends on a robust perception system that differentiates traversable from non-traversable terrain. Typically, this depends on a semantic understanding which is based on supervised learning from images annotated by a human expert. This requires a significant investment in human time, assumes correc...

A robotic platform for mobile manipulation needs to satisfy two contradicting requirements for many real-world applications: A compact base is required to navigate through cluttered indoor environments, while the support needs to be large enough to prevent tumbling or tip over, especially during fast manipulation operations with heavy payloads or f...

We describe an optimization-based framework to perform complex locomotion skills for robots with legs and wheels. The generation of complex motions over a long-time horizon often requires offline computation due to current computing constraints and is mostly accomplished through trajectory optimization (TO). In contrast, model predictive control (M...

In recent years, reinforcement learning (RL) has shown outstanding performance for locomotion control of highly articulated robotic systems. Such approaches typically involve tedious reward function tuning to achieve the desired motion style. Imitation learning approaches such as adversarial motion priors aim to reduce this problem by encouraging a...

Autonomous exploration of subterranean environments constitutes a major frontier for robotic systems, as underground settings present key challenges that can render robot autonomy hard to achieve. This problem has motivated the DARPA Subterranean Challenge, where teams of robots search for objects of interest in various underground environments. In...

Autonomous exploration of subterranean environments constitutes a major frontier for robotic systems as underground settings present key challenges that can render robot autonomy hard to achieve. This has motivated the DARPA Subterranean Challenge, where teams of robots search for objects of interest in various underground environments. In response...

We present a model predictive controller (MPC) that automatically discovers collision-free locomotion while simultaneously taking into account the system dynamics, friction constraints, and kinematic limitations. A relaxed barrier function is added to the optimization's cost function, leading to collision avoidance behavior without increasing the p...

Our paper proposes a model predictive controller as a single-task formulation that simultaneously optimizes wheel and torso motions. This online joint velocity and ground reaction force optimization integrates a kinodynamic model of a wheeled quadrupedal robot. It defines the single rigid body dynamics along with the robot's kinematics while treati...

Compared to wheeled vehicles, legged systems have a vast potential to traverse challenging terrain. To exploit the full potential, it is crucial to tightly integrate terrain perception for foothold planning. We present a hierarchical locomotion planner together with a foothold optimizer that finds locally optimal footholds within an elevation map....

Legged robots are exceedingly versatile and have the potential to navigate complex, confined spaces due to their many degrees of freedom. As a result of the computational complexity , there exist no online planners for perceptive whole body locomotion of robots in tight spaces. In this paper, we present a new method for perceptive planning for mult...

Wheeled-legged robots are an attractive solution for versatile locomotion in challenging terrain. They combine the speed and efficiency of wheels with the ability of legs to traverse challenging terrain. In this paper, we present a trajectory optimization formulation for wheeled-legged robots that optimizes over the base and wheels' positions and f...

Wheeled-legged robots have the potential for highly agile and versatile locomotion. The combination of legs and wheels might be a solution for any real-world application requiring rapid, and long-distance mobility skills on challenging terrain. In this paper, we present an online trajectory optimization framework for wheeled quadrupedal robots capa...

Wheeled-legged robots have the potential for highly agile and versatile locomotion. The combination of legs and wheels might be a solution for any real-world application requiring rapid, and long-distance mobility skills on challenging terrain. In this paper, we present an online trajectory optimization framework for wheeled quadrupedal robots capa...

The task of robotic mobile manipulation poses several scientific challenges that need to be addressed to execute complex manipulation tasks in unstructured environments, in which collaboration with humans might be required. Therefore, we present ALMA, a motion planning and control framework for a torque-controlled quadrupedal robot equipped with a...

Legged robots have the ability to adapt their walking posture to navigate confined spaces due to their high degrees of freedom. However, this has not been exploited in most common multilegged platforms. This paper presents a deformable bounding box abstraction of the robot model, with accompanying mapping and planning strategies, that enable a legg...

Legged robots have the ability to adapt their walking posture to navigate confined spaces due to their high degrees of freedom. However, this has not been exploited in most common multilegged platforms. This paper presents a deformable bounding box abstraction of the robot model, with accompanying mapping and planning strategies, that enable a legg...

We show dynamic locomotion strategies for wheeled quadrupedal robots, which combine the advantages of both walking and driving. The developed optimization framework tightly integrates the additional degrees of freedom introduced by the wheels. Our approach relies on a zero-moment point based motion optimization which continuously updates reference...

Legged robots have the ability to adapt their walking posture to navigate confined spaces due to their high degrees of freedom. However, this has not been exploited in most common multilegged platforms. This paper presents a deformable bounding box abstraction of the robot model, with accompanying mapping and planning strategies, that enable a legg...

We show dynamic locomotion strategies for wheeled quadrupedal robots, which combine the advantages of both walking and driving. The developed optimization framework tightly integrates the additional degrees of freedom introduced by the wheels. Our approach relies on a zero-moment point based motion optimization which continuously updates reference...

We present a trajectory optimizer for quadrupedal robots with actuated wheels. By solving for angular, vertical, and planar components of the base and feet trajectories in a cascaded fashion and by introducing a novel linear formulation of the zero-moment point (ZMP) balance criterion, we rely on quadratic programming only, thereby eliminating the...

The invention of the wheel is one of the major technological advances of humankind. In daily life, it enables us to move faster and more efficiently compared to leg-based locomotion. However, the latter is more versatile and offers the possibility to negotiate challenging environments. Combining both strategies into one system offers great possibil...

Traditional legged robots are capable of traversing challenging terrain, but lack of energy efficiency when compared to wheeled systems operating on flat environments. The combination of both locomotion domains overcomes the trade-off between mobility and efficiency. Therefore, this paper presents a novel motion planner and controller which togethe...

This paper provides insight into the application of the quadrupedal robot ANYmal in outdoor missions of industrial inspection (ARGOS Challenge) and search and rescue (European Robotics League (ERL) Emergency Robots). In both competitions, the legged robot had to autonomously and semi-autonomously navigate in real-world scenarios to complete high-le...

Conventional skid or wheel based helicopter landing gears severely limit off-field landing possibilities, which are crucial when operating in scenarios such as mountain rescue. In this context, slopes beyond 8° and small obstacles can already pose a substantial hazard. An adaptive landing gear is proposed to overcome these limitations. It consists...

Legged robots are an efficient alternative for navigation in challenging terrain. In this paper we describe Weaver, a six legged robot that is designed to perform autonomous navigation in unstructured terrain. It uses stereo vision and proprioceptive sensing based terrain perception for adaptive control while using visual-inertial odometry for auto...

Robots working in natural, urban, and industrial settings need to be able to navigate challenging environments. In this paper, we present a motion planner for the perceptive rough-terrain locomotion with quadrupedal robots. The planner finds safe footholds along with collision-free swing-leg motions by leveraging an acquired terrain map. To this en...

Autonomous robotic inspection of industrial sites offers a huge potential with respect to increasing human safety and operational efficiency. The present paper provides an insight into the approach taken by team LIO during the ARGOS Challenge. In this international competition, the legged robot ANYmal was equipped with a sensor head to perform visu...

Traditional legged robots are capable of traversing challenging terrain, but lack of energy efficiency when compared to wheeled systems operating on flat environments. The combination of both locomotion domains overcomes the trade-off between mobility and efficiency. Therefore, this paper presents a novel motion planner and controller which togethe...

This paper provides a system overview about ANYmal, a quadrupedal robot developed for operation in harsh environments. The 30 kg, 0.5 m tall robotic dog was built in a modular way for simple maintenance and user-friendly handling, while focusing on high mobility and dynamic motion capability. The system is tightly sealed to reach IP67 standard and...

To address the goal of locomotion in very complex and difficult terrains, the authors are developing a new class of Ultralight Legged Robots. This paper presents the Multilegged Autonomous eXplorer (MAX), an ultralight, six-legged robot for traversal and exploration of challenging indoor and outdoor environments. The design of MAX emphasizes a low...

This work introduces a novel hybrid control architecture for a hexapod platform (Weaver), making it capable of autonomously navigating in uneven terrain. The main contribution stems from the use of vision-based exte- roceptive terrain perception to adapt the robot’s locomotion parameters. Avoiding computationally expensive path planning for the ind...

Legged robots such as hexapods have the potential to traverse unstructured terrain. This paper introduces a novel hexapod robot (Weaver) using a hierarchical controller, with the ability to efficiently traverse uneven and inclined terrain. The robot has five joints per leg and 30 degrees of freedom overall. The two redundant joints improve the loco...

The ability to traverse uneven terrain is one of the key advantages of legged robots. However, their effectiveness relies on selecting appropriate gait parameters, such as stride height and leg stiffness. The optimal parameters highly depend on the characteristics of the terrain. This work presents a novel stereo vision based terrain sensing method...