We present a real-time algorithm which can recover the 3D trajectory of a monocular camera, moving rapidly through a previously unknown scene. Our system, which we dub MonoSLAM, is the first successful application of the SLAM methodology from mobile robotics to the "pure vision" domain of a single uncontrolled camera, achieving real time but drift-free performance inaccessible to structure from motion approaches. The core of the approach is the online creation of a sparse but persistent map of natural landmarks within a probabilistic framework. Our key novel contributions include an active approach to mapping and measurement, the use of a general motion model for smooth camera movement, and solutions for monocular feature initialization and feature orientation estimation. Together, these add up to an extremely efficient and robust algorithm which runs at 30 Hz with standard PC and camera hardware. This work extends the range of robotic systems in which SLAM can be usefully applied, but also opens up new areas. We present applications of MonoSLAM to real-time 3D localization and mapping for a high-performance full-size humanoid robot and live augmented reality with a hand-held camera

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MonoSLAM: Real-Time Single Camera SLAM

We introduce a new method of a biped walking pattern generation by using a preview control of the zero-moment point (ZMP). First, the dynamics of a biped robot is modeled as a running cart on a table which gives a convenient representation to treat ZMP. After reviewing conventional methods of ZMP based pattern generation, we formalize the problem as the design of a ZMP tracking servo controller. It is shown that we can realize such controller by adopting the preview control theory that uses the future reference. It is also shown that a preview controller can be used to compensate the ZMP error caused by the difference between a simple model and the precise multibody model. The effectiveness of the proposed method is demonstrated by a simulation of walking on spiral stairs.

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Biped walking pattern generation by using preview control of zero-moment point

From exploring planets to cleaning homes, the reach and versatility of robotics is vast. The integration of actuation, sensing and control makes robotics systems powerful, but complicates their simulation. This paper introduces a versatile, scalable, yet powerful general-purpose robot simulation framework called V-REP. The paper discusses the utility of a portable and flexible simulation framework that allows for direct incorporation of various control techniques. This renders simulations and simulation models more accessible to a general-public, by reducing the simulation model deployment complexity. It also increases productivity by offering built-in and ready-to-use functionalities, as well as a multitude of programming approaches. This allows for a multitude of applications including rapid algorithm development, system verification, rapid prototyping, and deployment for cases such as safety/remote monitoring, training and education, hardware control, and factory automation simulation.

V-REP: A versatile and scalable robot simulation framework

It is known that for a large magnitude push a human or a humanoid robot must take a step to avoid a fall. Despite some scattered results, a principled approach towards "when and where to take a step" has not yet emerged. Towards this goal, we present methods for computing capture points and the capture region, the region on the ground where a humanoid must step to in order to come to a complete stop. The intersection between the capture region and the base of support determines which strategy the robot should adopt to successfully stop in a given situation. Computing the capture region for a humanoid, in general, is very difficult. However, with simple models of walking, computation of the capture region is simplified. We extend the well-known linear inverted pendulum model to include a flywheel body and show how to compute exact solutions of the capture region for this model. Adding rotational inertia enables the humanoid to control its centroidal angular momentum, much like the way human beings do, significantly enlarging the capture region. We present simulations of a simple planar biped that can recover balance after a push by stepping to the capture region and using internal angular momentum. Ongoing work involves applying the solution from the simple model as an approximate solution to more complex simulations of bipedal walking, including a 3D biped with distributed mass.

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Capture Point: A Step toward Humanoid Push Recovery

For 3D walking control of a biped robot we analyze the dynamics of a 3D inverted pendulum in which motion is constrained to move along an arbitrarily defined plane. This analysis yields a simple linear dynamics, the 3D linear inverted pendulum mode (3D-LIPM). Geometric nature of trajectories under the 3D-LIPM and a method for walking pattern generation are discussed. A simulation result of a walking control using a 12-DOF biped robot model is also shown.

The 3D linear inverted pendulum mode: a simple modeling for a biped walking pattern generation

This article explains a control system, which stabilizes running biped robot HRP-2LR. The robot uses prescribed running pattern calculated by resolved momentum control, and a running controller stabilizes the system against disturbances. The running controller consists of posture stabilization, inverted pendulum stabilization, contact torque control, impact absorbing control, foot vertical force control and torque distribution control. Applying the proposed controller, HRP-2LR could successfully run with average speed of 0.16(m/s) repeating flight phase of 0.06 (s) and support phase of 0.3 (s).

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A Running Controller of Humanoid Biped HRP-2LR

In this paper, realtime control of dynamic biped locomotion using sensor information is investigated. The authors used an ultrasonic range sensor mounted on the robot to measure the distance from the robot to the ground surface. During the walking control, the sensor data is converted into a simple representation of the ground profile in realtime. The authors also developed a control architecture based on the linear inverted pendulum mode which they proposed previously for dynamic walking control. Combining the sensory system and the control system enabled the authors' biped robot, Meltran II, to walk over ground of unknown profile successfully.

Adaptive gait control of a biped robot based on realtime sensing of the ground profile

An experimental study of a biped robot is presented. A new scheme, named the "linear inverted pendulum mode" is utilized for controlling biped walking on rugged terrain. We developed a 6 d.o.f. biped robot "Meltran II" which has light weight legs and moves in a two dimensional vertical plane. To check the effects not well discussed in the theory, we carried out two experiments, the support phase experiment and the support exchange experiment. The support phase experiment was carried out to check the actual dynamics of biped walking when using the proposed control. It was shown that the dynamics of the robot can be regarded as linear even though the mass of the legs, which was neglected in the theory, exists, The support exchange experiment was performed to check leg support exchange. We found that a smooth leg support exchange is achieved by making the foot contact with a certain vertical speed and holding two leg support for a certain short period. Based on these results, a whole biped control system was implemented. In our experiment the robot walked over a box of 3.5 cm height at a speed of 20 cm/s.

Experimental study of biped dynamic walking in the linear inverted pendulum mode

Aiming for a humanoid robot of the next generation, we have been developing a biped which can jump and run. This paper introduces biped robot HRP-2LR and its hopping with both legs as our first attempt towards running. Using a dynamic model of HRP-2LR, hopping patterns are pre-calculated so that it follows the desired profiles of the total linear and angular momentum. For this purpose we used resolved momentum control. Adding small modifications to negotiate the difference between the model and the real hardware, we successfully realized a steady hopping motion of 0.06 [s] flight phase and 0.5 [s] support phase. A hopping with forward velocity of 15 [mm/s] was also realized. Finally, a running pattern of 0.06 [s] flight and 03 [s] support phase was tested. HRP-2LR could successfully run with average speed of 0.16 [m/s].

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A hop towards running humanoid biped

This paper presents a virtual humanoid robot platform (V-HRP for short) on which we can develop the identical controller for a virtual humanoid robot and its real counterpart. The unification of the controllers for the virtual and real robot has been realized by introducing software adapters for two robots respectively and employing ART-Linux on which real-time processing is available at the user level. Thanks to the unification, the controllers can share softwares with the dynamics simulator of V-HRP, including the parameter parser, kinematics and dynamics computations and the collision detector. This feature can make the development of the controllers more efficient and the developed controllers more reliable.

Shuuji Kajita

Papers

A Running Controller of Humanoid Biped HRP-2LR

Adaptive gait control of a biped robot based on realtime sensing of the ground profile

Experimental study of biped dynamic walking in the linear inverted pendulum mode

A hop towards running humanoid biped

Virtual humanoid robot platform to develop controllers of real humanoid robots without porting