Victor Barasuol

A reactive controller framework for quadrupedal locomotion on challenging terrain

We propose a reactive controller framework for robust quadrupedal locomotion, designed to cope with terrain irregularities, trajectory tracking errors and poor state estimation. The framework comprises two main modules: One related to the generation of elliptic trajectories for the feet and the other for control of the stability of the whole robot. We propose a task space CPG-based trajectory generation that can be modulated according to terrain irregularities and the posture of the robot trunk. To improve the robots stability, we implemented a null space based attitude control for the trunk and a push recovery algorithm based on the concept of capture points. Simulations and experimental results on the hydraulically actuated quadruped robot HyQ will be presented to demonstrate the effectiveness of our framework.

Towards versatile legged robots through active impedance control

Robots with legs and arms have the potential to support humans in dangerous, dull or dirty tasks. A major motivation behind research on such robots is their potential versatility. However, these robots come at a high price in mechanical and control complexity. Hence, until they can demonstrate a clear advantage over their simpler counterparts, robots with arms and legs will not fulfill their true potential. In this paper, we discuss the opportunities for versatile robots that arise by actively controlling the mechanical impedance of joints and particularly legs. In contrast to passive elements such as springs, active impedance is achieved by torque-controlled joints allowing real-time adjustment of stiffness and damping. Adjustable stiffness and damping in real-time is a fundamental building block towards versatility. Experiments with our 80 kg hydraulic quadruped robot HyQ demonstrate that active impedance alone (i.e. no springs in the structure) can successfully emulate passively compliant elements during highly dynamic locomotion tasks (running, jumping and hopping); and that no springs are needed to protect the actuation system. Here we present results of a flying trot, also referred to as a running trot. To the best of the authors’ knowledge this is the first time a flying trot has been successfully implemented on a robot without passive elements such as springs. A critical discussion on the pros and cons of active impedance concludes the paper. This article is an extension of our previous work presented at the International Symposium on Robotics Research (ISRR) 2013.

LOCAL REFLEX GENERATION FOR OBSTACLE NEGOTIATION IN QUADRUPEDAL LOCOMOTION

Legged robots that dynamically locomote through rough terrain need to constantly handle unpredicted collisions (e.g. foot stumbling due to an obstacle) due to the unstructured nature of the environment. If these disturbances are strong enough they can cause errors in the robot’s trunk that are difficult to control with a common feedback-based controller, imposing a serious risk to the overall system stability. The impulsive nature of such disturbances demands a very short reaction time, especially in case of dynamic gaits (trot, gallop, etc.). A quick reaction becomes increasingly crucial when the robot is deprived of reliable visual feedback (e.g. smoky areas or thick vegetation) or when an accurate map of the environment is not available. In this paper we propose a local elevator reflex which enables the robot to reactively overcome high obstacles. The reflex is implemented and experimentally evaluated on the hydraulic quadruped HyQ. We demonstrate the feasibility and effectiveness of our approach showing that the robot is able to step over a platform of 11cm height (14% of the leg length) without prior knowledge of the terrain.

Quadruped robot trotting over irregular terrain assisted by stereo-vision

Legged robots have the potential to navigate in challenging terrain, and thus to exceed the mobility of wheeled vehicles. However, their control is more difficult as legged robots need to deal with foothold computation, leg trajectories and posture control in order to achieve successful navigation. In this paper, we present a new framework for the hydraulic quadruped robot HyQ, which performs goal-oriented navigation on unknown rough terrain using inertial measurement data and stereo-vision. This work uses our previously presented reactive controller framework with balancing control and extends it with visual feedback to enable closed-loop gait adjustment. On one hand, the camera images are used to keep the robot walking towards a visual target by correcting its heading angle if the robot deviates from it. On the other hand, the stereo camera is used to estimate the size of the obstacles on the ground plane and thus the terrain roughness. The locomotion controller then adjusts the step height and the velocity according to the size of the obstacles. This results in a robust and autonomous goal-oriented navigation over difficult terrain while subject to disturbances from the ground irregularities or external forces. Indoor and outdoor experiments with our quadruped robot show the effectiveness of this framework.

Onboard perception-based trotting and crawling with the Hydraulic Quadruped Robot (HyQ)

This paper presents a framework developed to increase the autonomy and versatility of a large (~75kg) hydraulically actuated quadrupedal robot. It combines onboard perception with two locomotion strategies, a dynamic trot and a static crawl gait. This way the robot can perceive its environment and arbitrate between the two behaviours according to the situation at hand. All computations are performed on-board and are carried out in two separate computers, one handles the high-level processes while the other is concerned with the low-level hard real-time control. The perception and subsequently the appropriate gait modifications are performed autonomously. We present outdoor experimental trials of the robot trotting over unknown terrain, perceiving a large obstacle, altering its behaviour to the cautious crawl gait and stepping onto the obstacle. This allows the robot to locomote quickly on relatively flat terrain and gives the robot the ability to overcome large irregular obstacles when required.

Vision enhanced reactive locomotion control for trotting on rough terrain

Legged robots have the potential to navigate in more challenging terrain than wheeled robots do. Unfortunately, their control is more difficult because they have to deal with the traditional mapping and path planning problems, as well as foothold computation, leg trajectories and posture control in order to achieve successful navigation. Many parameters need to be adjusted in real time to keep the robot stable and safe while it is moving. In this paper, we will present a new framework for a quadruped robot, which performs goal-oriented navigation on unknown rough terrain by using inertial measurement data and stereo vision. This framework includes perception and control, and allows the robot to navigate in a straight line forward to a visual goal in a difficult environment. The developed rough terrain locomotion system does not need any mapping or path planning: the stereo camera is used to visually guide the robot and evaluate the terrain roughness and an inertial measurement unit (IMU) is used for posture control. This new framework is an important step forward to achieve fully autonomous navigation because in the case of problems in the SLAM mapping, a reactive locomotion controller is always active. This ensures stable locomotion in rough terrain, by combining direct visual feedback and inertial measurements. By implementing this controller, an autonomous navigation system has been developed, which is goal-oriented and overcomes disturbances from the ground, the robot weight, or external forces. Indoor and outdoor experiments with our quadruped robot show the effectiveness and the robustness of this framework.

Probabilistic Contact Estimation and Impact Detection for State Estimation of Quadruped Robots

Reliable state estimation is crucial for stable planning and control of legged locomotion. A fundamental component of a state estimator in legged platforms is Leg Odometry, which only requires information about kinematics and contacts. Many legged robots use dedicated sensors on each foot to detect ground contacts. However, this choice is impractical for many agile legged robots in field operations, as these sensors often degrade and break. Instead, this paper focuses on the development of a robust Leg Odometry module, which does not require contact sensors. The module estimates the probability of reliable contact and detects foot impacts using internal force sensing. This knowledge is then used to improve the kinematics-inertial state estimate of the robots base. We show how our approach can reach comparable performance to systems with foot sensors. Extensive experimental results lasting over 1 h are presented on our 85

ACTUATOR SIZING FOR HIGHLY-DYNAMIC QUADRUPED ROBOTS BASED ON SQUAT JUMPS AND RUNNING TROTS

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WCPG: A Central Pattern Generator for Legged Robots Based on Workspace Intentions

quadrupedal robot HyQ carrying out a variety of gaits.

VALIDATION OF COMPUTER SIMULATIONS OF THE HyQ ROBOT

It is challenging to design a quadruped robot that can perform highly dynamic tasks like jumping and running. Estimating appropriate range of joint torques and velocities is essential for the selection of the leg actuators. Jumping and running are considered as extreme tasks that push the actuators to their limits. In this paper we proposed a simple method that allows a quadruped robot designer to obtain approximate peak joint torques and joint velocities needed for a running trot at various forward velocities and squat jumps at different heights. A SLIP model is used for the mapping of CoM trajectory of a quadruped robot during a running tort. Experiments for a squat jump and running trot are performed with the highly dynamic quadruped robot HyQ for the validation of the proposed approaches. A case study is also discussed to demonstrate the usage of proposed tool.