Humanoid Vertical Jumping Based on Force Feedback and Inertial Forces Optimization
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Proceedings of the 2005 IEEE International Conference on Robotics and Automation Barcelona, Spain, April 2005 Humanoid Vertical Jumping based on Force Feedback and Inertial Forces Optimization Sophie Sakka and Kazuhito Yokoi AIST/CNRS Joint Japanese-French Robotics Research Laboratory (JRL) Intelligent Systems Research Institute (ISRI), AIST Central 2, 1-1-1 Umezono, Tsukuba 305-8568, Japan [email protected] Abstract— This paper proposes adapting human jumping to the robot dynamic balance stability limits [1][4] and dynamics to humanoid robotic structures. Data obtained from therefore allow new mobility patterns. human jumping phases and decomposition together with In order to generate walking patterns for different lo- ground reaction forces (GRF) are used as model references. Moreover, bodies inertial forces are used as task constraints comotion kinematics, the common way of most exist- while optimizing energy to determine the humanoid robot ing approaches is to precompute reference trajectories. posture and improve its jumping performances. Subsequent controller design and gains setting are then Index Terms— Humanoid robotics, jumping pattern gener- performed to make things work experimentally as close as ation, inertia optimization. possible to the theoretical algorithms. Handling of dynamic balance stability is mostly made with autonomous inde- I. INTRODUCTION pendent modules. For simple walking patterns, in known The humanoid robotic concept appeared in the last 20 environments, this way seems to work quite fine in many years. The Japanese institutions brought into the scene humanoid platforms and seems to be open to evolve to of the robotic research a considerable gap with the first more complex patterns. apparition of the Honda humanoid robot in the 1997. Since Similarly, using precomputed reference trajectory, this then, many robotic research organisms, from all around paper proposes a method for humanoid vertical jumping the world, considered to built humanoid platforms and (i.e. leading to a humanoid takeoff from ground). The humanoid national program are launched in many countries reference trajectory is derived from a thorough study of the (HRP, Robo-erectus, KHR [11], GuRoo, Dav, BH1 and way we, humans, jump. The humanoid reference jumping many others) [3], [5], [14], [15]. trajectory is designed to be as close as possible, under A humanoid robot is a complex redundent robotic system predefined constraints, to the human one which is derived having the particularity to be inspired from the human body from Ground Reaction Forces (GRF, and not from off structure kinematics, or even from human appearance in line trajectory monitoring); this is presented in section 2. some cases. Humanoids have a large number of degrees of Human jumping phases decomposition and GRF data are freedom (dof) and are usually modeled as tree structures used as references for pattern generation, this is presented grouping several open links chains. in section 3. In section 4, how bodies’ inertial forces can The tendency in reducing their weight and their size be optimized to determine the humanoid body posture in may lead to a fragile mechanical structure and since order to improve its jumping performances is discussed. the actuators are all together reduced in size they need These results are illustrated through a dynamic simulation reduction mechanism which generally cannot support high of a humanoid vertical jump using OpenHRP integrated impact forces. Consequently it becomes challenging to simulator with HRP-2 robot model. design controllers able to mimic some of the human- II. HUMANOID JUMPING REPRESENTATION like fast dynamics while meeting mechanical and actuators limitations. A. Procedure Up-to-now, humanoids platforms have been designed The humanoid vertical jump model uses the human jump for slow dynamics walking patterns. Consequently, ex- as a reference. There are many evident differences between perimental systems are limited in terms of locomotion the two “systems”; among them: foot bending capability, diversity, namely the ones inducing fast dynamics. This bodies mass repartition, joints and muscles quantity and is because of their technological design limitations. Fast characteristics, compliance, shock absorption capabilities. dynamic gaits, for example running or jumping (or more Therefore the human reference model provides the only precisely, jumping for running [17], [13], [9], are still external output of the human jump, i.e. the produced actively under investigation and spectacular results have vertical acceleration of the center of mass (CoM) with the recently been produced with ASIMO running [6]. Dynamic desired flight height. As we will see, we will make use equilibrium unbalance approaches for full body pattern of these data that are obtained by measuring the vertical motion definitions are still being formulated, even if some component of the feet/ground reaction force together with recent results for new mobility patterns tend to get closer the motion. Other parameters, such as the human joints 0-7803-8914-X/05/$20.00 ©2005 IEEE. 3752 angle or joints speed values are not considered whereas torque variation in the knees using a feet retraction other studies, such as in [2][7][16] considered these data procedure. on their developed mimetic approaches. This paper focuses on the study of launching stage of the vertical jump, and more precisely defines a jumping function which groups jumping phase and takeoff impulse described thereafter. The launching stage of the jump is fundamental as it allows to meet the jump requirements (desired height, flight and landing stability) while mini- mizing robot actuators resources. This stage is divided in three successive phases: Fig. 2. Ground reaction force for a human maximal capacities vertical jump with counter-movement obtained using a force platform [12] These three main phases are spotted on Fig. 2, which shows an experimental curve of the GRF for human maximal jump with counter-movement measured using a force platform (a) Lift effect (b) Compression effect (c) Lift effect [12]. The counter-movement is labeled from a to c, where Fig. 1. Qualitative effects of arm-swing. the system is stabilized in jumping configuration (figure 1.a). The jumping phase is between c and d and the final impulse is around point d. The relation linking acceleration 1) Counter movement phase: it mainly simulates the to reaction forces is given by the system of fundamental 1 human muscular explosive jumping movement. On equations of motion before takeoff, that is: robots, this phase can be associated to initial launch- ext mX¨ G F ing configuration. For humans, the way this phase = (1) Mext is performed influences muscle conditions, conse- δr/Σ G G/Σ G quently the performance of one’s jump. This is not where m denotes the total mass of the humanoid robot, the case of humanoids since they are robotics systems X¨ G is the Cartesian acceleration vector of the system CoM and the actuator can produce max torques from any G, δr/Σ(G) is the system resulting dynamic momentum in static configuration (i.e. in the contrary to muscles, Σ ext = ext = + the reference frame noted . F Fi R mg and they do not require a specific “warp-up” phase). ext = ext MG/Σ MGi/Σ are respectively the resulting external 2) Jumping phase: The jumping phase denotes the forces and momentum applied to the body and expressed 3 −2 propulsion phase of the jump. The body is subject at the CoM. g = −9.81xΣ [m.s ] denotes the gravity 3 to rising vertical acceleration until its speed reaches acceleration vector (xΣ denotes the vertical component of 86% of the takeoff desired speed for a medium the reference world frame Σ). jump. This proportion increases when the jump is Considering Eq. 1, CoM acceleration and GRF values required to reach more important heights, i.e. when have the same profile of evolution with time. Then, ac- one needs to get close to the maximal biological celeration of the CoM shows a linear profile through the capabilities. Movement amplitude (feet/hip distance whole jumping function (which includes jumping phase between the jumping initial configuration and the and takeoff impulse). The optimization of trajectories de- jumping extension configuration) and the value of scribed in the following sections concentrates on the study vertical acceleration are the two key parameters that of this particular function, but first we precise thereafter characterize the jumping phase. the influent parameters of the jump. 3) Takeoff impulse: this phase lasts the shortest time; The parameters influencing the humanoid jump are il- it is the most demanding in matter of system power lustrated on Fig. 3. resources. Takeoff impulse has two aims: the first The jump (or flight) height denotes the desired jump one is to adapt precisely the actual body speed to requirements. It corresponds to the jumping target and is the required takeoff speed in order to reach the given by the user or the embedded planner. The jump target desired jump height, the second one counterbalances can be defined either from a hand reaching target or a feet the inertial effects created by the discontinuity of the height target according to the task. Our study focuses on GRF at the takeoff time. This allows to reduce brutal the last situation (i.e. the desired feet height). The flight height is influenced by, see Fig. 3: 1All along the paper we are using the terminology adopted in the bio- • mechanics field, we think that meaning can be guessed easily from the the technological limitations (for exemple motors lim- employed terms [18]. its), which also define other important parameters such 3753 FLIGHT HEIGHT between the instant at takeoff and at maximal peak of the jump leads to the expression of the desired CoM speed at ˙ takeoff Xto according to the desired maximal peak xmax: Technology Vertical velocity ˙ 2 Gravity =2 ( max − ( )) constraints at takeoff Xto g x X tto (2) The CoM vertical trajectory, velocity and acceleration are Change in Initial velocity then described by the traditional free flight rigid body vertical velocity from approach motion equations.