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This paper presents the design of the hydraulically actuated quadruped robot HyQ2Max. HyQ2Max is an evolution of the 80kg agile and versatile robot HyQ. Compared to HyQ, the new robot needs to be more rugged, more powerful and extend the existing locomotion skills with self-righting capability. Since the robot's actuation system has an impact on many aspects of the overall design/specifications of the robot (e.g. payload, speed, torque, overall mass, compactness), this paper will pay special attention to the selection and sizing of the joint actuators. To obtain meaningful joint requirements for the new machine, we simulated 7 characteristic motions that cover a wide range of required behaviors of an agile rough terrain robot, including trotting on rough terrain, stair climbing, push recovery, self-righting, etc. We will describe how to use the obtained joint requirements for the selection of the hydraulic actuator types, four-bar linkage parameters and valve size. Poorly sized actuators may lead to limited robot capabilities or higher cost, weight, energy consumption and cooling requirements. The main contributions of this paper are (1) a novel design of an agile quadruped robot capable of performing trotting/crawling over flat/uneven terrain, balancing and self-righting; (2) a detailed method to find suitable hydraulic cylinder/valve properties and linkage parameters with a specific focus on optimizing the actuator areas; and (3) to the best knowledge of the authors, the most complete review of hydraulic quadruped robots.

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.

Many algorithms for control, optimization and estimation in robotics depend on derivatives of the underlying system dynamics, e.g. to compute linearizations, sensitivities or gradient directions. However, we show that when dealing with Rigid Body Dynamics, these derivatives are difficult to derive analytically and to implement efficiently. To overcome this issue, we extend the modelling tool 'RobCoGen' to be compatible with Automatic Differentiation. Additionally, we propose how to automatically obtain the derivatives and generate highly efficient source code. We highlight the flexibility and performance of the approach in two application examples. First, we show a Trajectory Optimization example for the quadrupedal robot HyQ, which employs auto-differentiation on the dynamics including a contact model. Second, we present a hardware experiment in which a 6 DoF robotic arm avoids a randomly moving obstacle in a go-to task by fast, dynamic replanning. This paper is an extended version of [1].