Learning Image-Conditioned Dynamics Models for Control of Under-actuated Legged Millirobots

Millirobots are a promising robotic platform for many applications due to their small size and low manufacturing costs. Legged millirobots, in particular, can provide increased mobility in complex environments and improved scaling of obstacles. However, controlling these small, highly dynamic, and underactuated legged systems is difficult. Hand-engineered controllers can sometimes control these legged millirobots, but they have difficulties with dynamic maneuvers and complex terrains. We present an approach for controlling a real-world legged millirobot that is based on learned neural network models. Using less than 17 minutes of data, our method can learn a predictive model of the robot's dynamics that can enable effective gaits to be synthesized on the fly for following user-specified waypoints on a given terrain. Furthermore, by leveraging expressive, high-capacity neural network models, our approach allows for these predictions to be directly conditioned on camera images, endowing the robot with the ability to predict how different terrains might affect its dynamics. This enables sample-efficient and effective learning for locomotion of a dynamic legged millirobot on various terrains, including gravel, turf, carpet, and styrofoam. Experiment videos can be found at https://sites.google.com/view/imageconddy

On Advanced Mobility Concepts for Intelligent Planetary Surface Exploration

Surface exploration by wheeled rovers on Earth's Moon (the two Lunokhods) and Mars (Nasa's Sojourner and the two MERs) have been followed since many years already very suc-cessfully, specifically concerning operations over long time. However, despite of this success, the explored surface area was very small, having in mind a total driving distance of about 8 km (Spirit) and 21 km (Opportunity) over 6 years of operation. Moreover, ESA will send its ExoMars rover in 2018 to Mars, and NASA its MSL rover probably this year. However, all these rovers are lacking sufficient on-board intelligence in order to overcome longer dis-tances, driving much faster and deciding autonomously on path planning for the best trajec-tory to follow. In order to increase the scientific output of a rover mission it seems very nec-essary to explore much larger surface areas reliably in much less time. This is the main driver for a robotics institute to combine mechatronics functionalities to develop an intelligent mo-bile wheeled rover with four or six wheels, and having specific kinematics and locomotion suspension depending on the operational terrain of the rover to operate. DLR's Robotics and Mechatronics Center has a long tradition in developing advanced components in the field of light-weight motion actuation, intelligent and soft manipulation and skilled hands and tools, perception and cognition, and in increasing the autonomy of any kind of mechatronic systems. The whole design is supported and is based upon detailed modeling, optimization, and simula-tion tasks. We have developed efficient software tools to simulate the rover driveability per-formance on various terrain characteristics such as soft sandy and hard rocky terrains as well as on inclined planes, where wheel and grouser geometry plays a dominant role. Moreover, rover optimization is performed to support the best engineering intuitions, that will optimize structural and geometric parameters, compare various kinematics suspension concepts, and make use of realistic cost functions like mass and consumed energy minimization, static sta-bility, and more. For self-localization and safe navigation through unknown terrain we make use of fast 3D stereo algorithms that were successfully used e.g. in unmanned air vehicle ap-plications and on terrestrial mobile systems. The advanced rover design approach is applica-ble for lunar as well as Martian surface exploration purposes. A first mobility concept ap-proach for a lunar vehicle will be presented

Active Exploration of Surfaces for Legged Locomotion of Robots

This paper presents some results of an ongoing research project in the GRASP Lab in the area of active exploration and perception for the legged locomotion of robots. We propose an active perceptual scheme that is based on the ability of the robot to extract material properties from a surface during locomotion. This ability is provided to the robotic system through a compliant sensing device which is used to monitor the response of the surface when exploratory procedures are executed during the stepping and walking motions of the leg. Such a system will actively perceive changes in the surfaces properties and prevent the robot from slipping, falling, or sinking during locomotion. The paper describes the proposed perceptual scheme, the system set-up, and the implementation of the exploratory procedures

An Overview of Legged Robots

The objective of this paper is to present the evolution and the state-of-theart in the area of legged locomotion systems. In a first phase different possibilities for mobile robots are discussed, namely the case of artificial legged locomotion systems, while emphasizing their advantages and limitations. In a second phase an historical overview of the evolution of these systems is presented, bearing in mind several particular cases often considered as milestones on the technological and scientific progress. After this historical timeline, some of the present day systems are examined and their performance is analyzed. In a third phase are pointed out the major areas for research and development that are presently being followed in the construction of legged robots. Finally, some of the problems still unsolved, that remain defying robotics research, are also addressed.N/

Robotic Exploration of Surfaces With a Compliant Wrist Sensor

This paper presents some results of an ongoing research project to investigate the components and modules that are necessary to equip a robot with exploratory capabilities. Of particular interest is the recovery of certain material properties from a surface, given minimal a priori information, with the intent to use this information to enable a robot to stand and walk stably on a surface that is unknown and unconstrained. To this end, exploratory procedures (ep\u27s) have been designed and implemented to recover penetrability, material hardness and surface roughness by exploring the surface using a compliant wrist sensor. A six degree-of-freedom compliant wrist sensor, which combines passive compliance and active sensing, has been developed to provide the necessary flexibility for force and contact control, as well as to provide accurate position control. This paper describes the compliant wrist and sensing mechanism design along with a hybrid control algorithm that utilizes the sensed information from the wrist to adjust the apparent stiffness of the end-effector as desired

Planetary rover technology development requirements

Planetary surface (including lunar) mobility and sampling capability is required to support proposed future National Aeronautics and Space Administration (NASA) solar system exploration missions. The NASA Office of Aeronautics and Space Technology (OAST) is addressing some of these technology needs in its base research and development program, the Civil Space Technology Initiative (CSTI) and a new technology initiative entitled Pathfinder. The Pathfinder Planetary Rover (PPR) and Sample Acquisition, Analysis and Preservation (SAAP) programs will develop and validate the technologies needed to enable both robotic and piloted rovers on various planetary surfaces. The technology requirements for a planetary roving vehicle and the development plans of the PPR and SAAP programs are discussed