Consider a differential-drive mobile robot equipped with an on-board exteroceptive sensor that can estimate its own motion, e. g., a range-finder. Calibration of this robot involves estimating six parameters: three for the odometry (radii and distance between the wheels) and three for the pose of the sensor with respect to the robot. After analyzing the observability of this problem, this paper describes a method for calibrating all parameters at the same time, without the need for external sensors or devices, using only the measurement of the wheel velocities and the data from the exteroceptive sensor. The method does not require the robot to move along particular trajectories. Simultaneous calibration is formulated as a maximum-likelihood problem and the solution is found in a closed form. Experimental results show that the accuracy of the proposed calibration method is very close to the attainable limit given by the Cramer-Rao bound

Abstract-The upcoming generation of humanoid robots will have to be equipped with state-of-the-art technical features along with high industrial quality, but they should also offer the prospect of effective physical human interaction. In this paper we introduce a new humanoid robot capable of interacting with a human environment and targeting industrial applications. Limitations are outlined and used together with the feedback from the DARPA Robotics Challenge, and other teams leading the field in creating new humanoid robots. The resulting robot is able to handle weights of 6 kg with an out-stretched arm, and has powerful motors to carry out fast movements. Its kinematics have been specially designed for screwing and drilling motions. In order to make interaction with human operators possible, this robot is equipped with torque sensors to measure joint effort and high resolution encoders to measure both motor and joint positions.The humanoid robotics field has reached a stage where robustness and repeatability is the next watershed. We believe that this robot has the potential to become a powerful tool for the research community to successfully navigate this turning point, as the humanoid robot HRP-2 was in its own time.

Abstract-For a differential-drive mobile robot equipped with an on-board range sensor, there are six parameters to calibrate: three for the odometry (radii and distance between the wheels), and three for the pose of the sensor with respect to the robot frame. This paper describes a method for calibrating all six parameters at the same time, without the need for external sensors or devices. Moreover, it is not necessary to drive the robot along particular trajectories. The available data are the measures of the angular velocities of the wheels and the range sensor readings. The maximum-likelihood calibration solution is found in a closed form.

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It is in general complex to consider the complete robot dynamics when planning trajectories for bipedal locomotion. We present an approach to trajectory planning, with the classical Linear Inverted Pendulum Model (LIPM), that takes explicit consideration of the unstable dynamics. We derive a relationship between initial state and the control input that ensures the overall system dynamics will converge to a stable steady state solution. This allows us to exploit the unstable dynamics to achieve system goals, while imposing constraints on certain degrees of freedom of the input and initial conditions. Based on this, we propose an approach to trajectory planning, and derive solutions for several typical applications. Experimental simulations using the REEM-C biped robot platform of Pal Robotics validate our approach.