Keep Rollin' - Whole-Body Motion Control and Planning for Wheeled Quadrupedal Robots

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 trajectories. The reference motions are tracked by a hierarchical whole-body controller which computes optimal generalized accelerations and contact forces by solving a sequence of prioritized tasks including the nonholonomic rolling constraints. Our approach has been tested on ANYmal, a quadrupedal robot that is fully torque-controlled including the non-steerable wheels attached to its legs. We conducted experiments on flat and inclined terrains as well as over steps, whereby we show that integrating the wheels into the motion control and planning framework results in intuitive motion trajectories, which enable more robust and dynamic locomotion compared to other wheeled-legged robots. Moreover, with a speed of 4 m/s and a reduction of the cost of transport by 83 % we prove the superiority of wheeled-legged robots compared to their legged counterparts.Comment: IEEE Robotics and Automation Letter

TAMOLS: Terrain-Aware Motion Optimization for Legged Systems

Terrain geometry is, in general, non-smooth, non-linear, non-convex, and, if perceived through a robot-centric visual unit, appears partially occluded and noisy. This work presents the complete control pipeline capable of handling the aforementioned problems in real-time. We formulate a trajectory optimization problem that jointly optimizes over the base pose and footholds, subject to a heightmap. To avoid converging into undesirable local optima, we deploy a graduated optimization technique. We embed a compact, contact-force free stability criterion that is compatible with the non-flat ground formulation. Direct collocation is used as transcription method, resulting in a non-linear optimization problem that can be solved online in less than ten milliseconds. To increase robustness in the presence of external disturbances, we close the tracking loop with a momentum observer. Our experiments demonstrate stair climbing, walking on stepping stones, and over gaps, utilizing various dynamic gaits.Comment: Accepted as regular T-RO pape

Dynamic Locomotion on Slippery Ground

Dynamic locomotion on unstructured and uneven terrain is a challenging task in legged robotics. Especially when it comes to slippery ground conditions, common state estimation and control algorithms suffer from the usual no-slip assumption. In fact, there has been only little research on this subject. This paper addresses the problem of slipping by treating slip detection and recovery tasks separately. Our contribution to the former is a probabilistic slip estimator based on aHidden Markov Model. In the second part of this paper, we propose impedance control and friction modulation as useful tools to recover stability during traction loss. We demonstrate the success of our estimation/control architecture by enabling ANYmal, a quadrupedal torque-controllable robot, to dynamically walk over slippery terrain

Dynamic locomotion through online nonlinear motion optimization for quadrupedal robots

This paper presents a realtime motion planning and control method which enables a quadrupedal robot to execute dynamic gaits including trot, pace and dynamic lateral walk, as well as gaits with full flight phases such as jumping, pronking and running trot. The proposed method also enables smooth transitions between these gaits. Our approach relies on an online ZMP based motion planner which continuously updates the reference motion trajectory as a function of the contact schedule and the state of the robot. The reference footholds for each leg are obtained by solving a separate optimization problem.The resulting optimized motion plans are tracked by a hierarchical whole-body controller. Our framework has been tested in simulation and on ANYmal, a fully torque-controllable quadrupedal robot, both in simulation and on the actual robot.ISSN:2377-376

Efficient Gait Selection for Quadrupedal Robots on the Moon and Mars

We present the outcome of a study on the energetic expenditure of quadrupedal gaits in the gravitational scenarios of Earth, Mars and the Moon. The study was performed in simulation on a fully controlled 30kg-class robot. We compared the mechanical power required for locomotion by using a static walking gait, dynamic gaits without full flight phases (trot, dynamic lateral walk) and dynamic gaits with full flight phases (running trot, pronk) at velocities up to 1 m/s. Additionally, we conducted a field test which compared the energetic expenditure and ground contact forces of a trot and running trot on a sandy terrain against the laboratory environment and the simulation results.Generally, gaits with full flight phases become increasingly efficient in reduced gravity scenarios. The study revealed that a running trot outperforms the gaits without full flight phases at forward velocities of 0.55 m/s on Mars and 0.4 m/s on the Moon. Executing a trot on the real robot showed that the energetic expenditure is 1.2-1.4 times higher on a coarse, heterogeneous sand compared to the lab environment. The field test revealed that the point feet design is not optimal for gaits with full flight phases on compressible soil due to high contact forces and increased ground penetration, which leads to stuck situations

Elevation Mapping for Locomotion and Navigation using GPU

Perceiving the surrounding environment is crucial for autonomous mobile robots. An elevation map provides a memory-efficient and simple yet powerful geometric representation of the terrain for ground robots. The robots can use this information for navigation in an unknown environment or perceptive locomotion control over rough terrain. Depending on the application, various post processing steps may be incorporated, such as smoothing, inpainting or plane segmentation. In this work, we present an elevation mapping pipeline leveraging GPU for fast and efficient processing with additional features both for navigation and locomotion. We demonstrated our mapping framework through extensive hardware experiments. Our mapping software was successfully deployed for underground exploration during DARPA Subterranean Challenge and for various experiments of quadrupedal locomotion

Perceptive Locomotion in Rough Terrain – Online Foothold Optimization

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. The map is generated in real-time from on-board depth sensors. We further propose a terrain-aware contact schedule to deal with actuator velocity limits. We validate the combined locomotion pipeline on our quadrupedal robot ANYmal with a variety of simulated and real-world experiments. We show that our method can cope with stairs and obstacles of heights up to 33% of the robot’s leg length.ISSN:2377-376

Dynamic Locomotion on Slippery Ground

ISSN:2377-376

Trajectory Optimization for Wheeled-Legged Quadrupedal Robots Using Linearized ZMP Constraints

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 zeromoment point balance criterion, we rely on quadratic programming only, thereby eliminating the need for nonlinear optimization routines. Yet, even for gaits containing full flight phases, we are able to generate trajectories for executing complex motions that involve simultaneous driving, walking, and turning. We verified our approach in simulations of the quadrupedal robot ANYmal equipped with wheels, where we are able to run the proposed trajectory optimizer at 50 Hz. To the best of our knowledge, this is the first time that such dynamic motions are demonstrated for wheeled-legged quadrupedal robots using an online motion planner