Simulation of an interlocking hydraulic direct-drive system for a biped walking robot

Biped robots with serial links driven by an electric motor experience problems because the motor and transmission are installed in each joint, causing the legs to become very heavy. Previous solutions involved robots using servo valves, a type of highly responsive proportional valve. However, high supply pressure is necessary to realize high responsiveness and the resulting energy losses are large. To address this problem, we proposed a hydraulic direct-drive system in which the pump controls the cylinder meter-in flow, while a proportional valve controls the meter-out flow. Furthermore, our hydraulic interlocking drive system connects two hydraulic direct-drive systems for biped humanoid robots and concentrates the pump output on one side cylinder. The meter-in flow rate of the other side cylinder is controlled by the meter-out flow rate of the cylinder on which the pump is concentrated. A comparison of the walking simulation performance with that of the conventional independent system shows that our proposed system reduces the motor output power by 24.3%. These results prove the feasibility of constructing a two-legged robot without having to incorporate highly responsive servo valves

Study on a bipedal walking robot that adapts to real-world obstacles and changing terrains

制度:新 ; 報告番号:甲3056号 ; 学位の種類:博士(工学) ; 授与年月日:2010/3/15 ; 早大学位記番号:新531

Walking in the uncanny valley: importance of the attractiveness on the acceptance of a robot as a working partner

The Uncanny valley hypothesis, which tells us that almost-human characteristics in a robot or a device could cause uneasiness in human observers, is an important research theme in the Human Robot Interaction (HRI) field. Yet, that phenomenon is still not well-understood. Many have investigated the external design of humanoid robot faces and bodies but only a few studies have focused on the influence of robot movements on our perception and feelings of the Uncanny valley. Moreover, no research has investigated the possible relation between our uneasiness feeling and whether or not we would accept robots having a job in an office, a hospital or elsewhere. To better understand the Uncanny valley, we explore several factors which might have an influence on our perception of robots, be it related to the subjects, such as culture or attitude toward robots, or related to the robot such as emotions and emotional intensity displayed in its motion. We asked 69 subjects (N = 69) to rate the motions of a humanoid robot (Perceived Humanity, Eeriness, and Attractiveness) and state where they would rather see the robot performing a task. Our results suggest that, among the factors we chose to test, the attitude toward robots is the main influence on the perception of the robot related to the Uncanny valley. Robot occupation acceptability was affected only by Attractiveness, mitigating any Uncanny valley effect. We discuss the implications of these findings for the Uncanny valley and the acceptability of a robotic worker in our society

Enabling Force Sensing During Ground Locomotion: A Bio-Inspired, Multi-Axis, Composite Force Sensor Using Discrete Pressure Mapping

This paper presents a new force sensor design approach that maps the local sampling of pressure inside a composite polymeric footpad to forces in three axes, designed for running robots. Conventional multiaxis force sensors made of heavy metallic materials tend to be too bulky and heavy to be fitted in the feet of legged robots, and vulnerable to inertial noise upon high acceleration. To satisfy the requirements for high speed running, which include mitigating high impact forces, protecting the sensors from ground collision, and enhancing traction, these stiff sensors should be paired with additional layers of durable, soft materials; but this also degrades the integrity of the foot structure. The proposed foot sensor is manufactured as a monolithic, composite structure composed of an array of barometric pressure sensors completely embedded in a protective polyurethane rubber layer. This composite architecture allows the layers to provide compliance and traction for foot collision while the deformation and the sampled pressure distribution of the structure can be mapped into three axis force measurement. Normal and shear forces can be measured upon contact with the ground, which causes the footpad to deform and change the readings of the individual pressure sensors in the array. A one-time training process using an artificial neural network is all that is necessary to relate the normal and shear forces with the multiaxis foot sensor output. The results show that the sensor can predict normal forces in the Z-axis up to 300 N with a root mean squared error of 0.66% and up to 80 N in the X- and Y-axis. The experiment results demonstrates a proof-of-concept for a lightweight, low cost, yet robust footpad sensor suitable for use in legged robots undergoing ground locomotion.United States. Defense Advanced Research Projects Agency. Maximum Mobility and Manipulation (M3) ProgramSingapore. Agency for Science, Technology and Researc

Bipedal walking trajectory energy minimization through a learned hip height trajectory

This thesis describes methods used to optimize energy consumption of an offine bipedal walking trajectories through hip height control. The experiments were carried out on a miniature humanoid robot within the simulation environment Webots. Zero Moment Point (ZMP) preview control methods were implemented in Matlab to produce a stable walking trajectory for the robot with a fixed hip height. The hip height trajectory was then developed using an observation based Q-learning method that consider both stability and energy consumption. Through the Q-learning methods there was approximately a 9% decrease in the average energy consumption. Additionally, an increase in stability was observed.M.S., Mechanical Engineering and Mechanics -- Drexel University, 201

Imprecise dynamic walking with time-projection control

We present a new walking foot-placement controller based on 3LP, a 3D model of bipedal walking that is composed of three pendulums to simulate falling, swing and torso dynamics. Taking advantage of linear equations and closed-form solutions of the 3LP model, our proposed controller projects intermediate states of the biped back to the beginning of the phase for which a discrete LQR controller is designed. After the projection, a proper control policy is generated by this LQR controller and used at the intermediate time. This control paradigm reacts to disturbances immediately and includes rules to account for swing dynamics and leg-retraction. We apply it to a simulated Atlas robot in position-control, always commanded to perform in-place walking. The stance hip joint in our robot keeps the torso upright to let the robot naturally fall, and the swing hip joint tracks the desired footstep location. Combined with simple Center of Pressure (CoP) damping rules in the low-level controller, our foot-placement enables the robot to recover from strong pushes and produce periodic walking gaits when subject to persistent sources of disturbance, externally or internally. These gaits are imprecise, i.e., emergent from asymmetry sources rather than precisely imposing a desired velocity to the robot. Also in extreme conditions, restricting linearity assumptions of the 3LP model are often violated, but the system remains robust in our simulations. An extensive analysis of closed-loop eigenvalues, viable regions and sensitivity to push timings further demonstrate the strengths of our simple controller