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

/pdf/monoslam-real-time-single-camera-slam-ydmj8dc1vj.pdf

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.

/pdf/biped-walking-pattern-generation-by-using-preview-control-of-84qdve2k8v.pdf

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.

/pdf/capture-point-a-step-toward-humanoid-push-recovery-12jssfk8t5.pdf

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

In this paper we present a humanoid robot, HRP-2P, which can walk, lie down and get up. We believe that HRP-2P (154 cm height and 58 kg weight) is the first humanoid robot that is the size of a human and can lie down and get up. Biped walking is realized by a walking pattern generator using a preview control and a feedback control. The lying down and getting up motions were made possible by HRP-2P's compact body with a waist joint and a novel motion controller.

The Human-size Humanoid Robot That Can Walk, Lie Down and Get Up

This work studies locomotion planning of humanoid robots to pass through narrow spaces. Humanoid robots can alter the style of the locomotion while wheeled robots can not. The proposed method generates a 3D local map from visual information and plans the appropriate locomotion based on the map from biped walking with the variable height and the width and from crawling.

/pdf/locomotion-planning-of-humanoid-robots-to-pass-through-a90surw1ig.pdf

Locomotion planning of humanoid robots to pass through narrow spaces

This paper proposes a method for a humanoid robot to generate 3D model of the environment using a stereo vision, find a movable space using it and plan feasible locomotion online. The model is generated by an accumulation of 3D grid maps which are made from the range data of the field of view obtained by a correlation based stereo vision. The locomotion is planned by an online whole body pattern generator which can modify robot’s waist height, an upper body posture and so on according to the size of the movable space.

/pdf/whole-body-locomotion-planning-of-humanoid-robots-based-on-a-69tl7a6iv3.pdf

Whole Body Locomotion Planning of Humanoid Robots based on a 3D Grid Map

We have developed a humanoid robot HRP-1S that is capable of simultaneous whole body motion control. In phase one of the Humanoid Robotics Project (HRP) of the Ministry of Economy, Trade and Industry of Japan, Honda R&D Co. Ltd has produced humanoid robot HRP-1 as a humanoid research platform to ease the development of good applications for humanoid robots in phase two of HRP. However, HRP-1 controls its legs and arms separately, and is not suitable for some applications. We modified the control hardware of HRP-1 and implemented our own control software. The modified robot was designated HRP-1S. The motion controller of HRP-1S is built in accordance with the plug-in architecture. We have developed some plug-ins including a real-time walking pattern generator (KWALK plug-in) and a reflex controller (STABILIZER plug-in) to maintain the dynamic balance of HRP-1S. In this paper, we present the system architecture of the control system of HRP-1S and several experimental results.

Experimental Study of Humanoid Robot HRP-1S

Aiming for a humanoid robot of the next generation, we have been developing a biped which can jump and run. This paper introduces a method of running pattern generation and running experiment of biped robot HRP-2LR. Based on the physical parameters of HRP-2LR, running 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. The vertical momentum is calculated considering the compliant elements in order to realize accurate flight duration. The horizontal momentum is calculated to satisfy the ZMP patterns given in advance. Using our pattern, HRP-2LR could successfully run with average speed of 0.16[m/s] with repeat flight phase 0.06 [s] and support phase 0.3 [s].

/pdf/a-running-experiment-of-humanoid-biped-3mnht15e4r.pdf

Shuuji Kajita

Papers

The Human-size Humanoid Robot That Can Walk, Lie Down and Get Up

Locomotion planning of humanoid robots to pass through narrow spaces

Whole Body Locomotion Planning of Humanoid Robots based on a 3D Grid Map

Experimental Study of Humanoid Robot HRP-1S

A running experiment of humanoid biped