Topic
Humanoid robot
About: Humanoid robot is a research topic. Over the lifetime, 14387 publications have been published within this topic receiving 243674 citations. The topic is also known as: 🤖.
Papers published on a yearly basis
Papers
More filters
••
09 Sep 2012TL;DR: A control scheme that allows a humanoid robot to perform a complex transportation scenario jointly with a human partner and takes over the leadership of the task to complete the scenario.
Abstract: In this paper, we propose a control scheme that allows a humanoid robot to perform a complex transportation scenario jointly with a human partner. At first, the robot guesses the human partner's intentions to proactively participate to the task. In a second phase, the human-robot dyad switches roles: the robot takes over the leadership of the task to complete the scenario. During this last phase, the robot is remotely controlled with a joystick. The scenario is realized on a real HRP-2 humanoid robot to assess the overall approach.
71 citations
••
TL;DR: A novel approach to plan foot placements for a humanoid robot according to kinematic tasks is presented and an algorithm to adapt the number of footsteps progressively to the kinematics goal is proposed.
Abstract: We present a novel approach to plan foot placements for a humanoid robot according to kinematic tasks. In this approach, the foot placements are determined by the continuous deformation of a robot motion including a locomotion phase according to the desired tasks. We propose to represent the motion by a virtual kinematic tree composed of a kinematic model of the robot and articulated foot placements. This representation allows us to formulate the motion deformation problem as a classical inverse kinematics problem on a kinematic tree. We first provide details of the basic scheme where the number of footsteps is given in advance and illustrate it with scenarios on the robot HRP-2. Then we propose a general criterion and an algorithm to adapt the number of footsteps progressively to the kinematic goal. The limits and possible extensions of this approach are discussed last.
71 citations
••
TL;DR: In this paper, a motion generation algorithm for legged robots is proposed to compute consistent contact forces and joint trajectories for a humanoid robot given predefined contact surfaces, and the motion generation process is decomposed into two alternating parts computing force and motion plans in coherence.
Abstract: Optimal control approaches in combination with trajectory optimization have recently proven to be a promising control strategy for legged robots. Computationally efficient and robust algorithms were derived using simplified models of the contact interaction between robot and environment such as the linear inverted pendulum model (LIPM). However, as humanoid robots enter more complex environments, less restrictive models become increasingly important. As we leave the regime of linear models, we need to build dedicated solvers that can compute interaction forces together with consistent kinematic plans for the whole-body. In this paper, we address the problem of planning robot motion and interaction forces for legged robots given predefined contact surfaces. The motion generation process is decomposed into two alternating parts computing force and motion plans in coherence. We focus on the properties of the momentum computation leading to sparse optimal control formulations to be exploited by a dedicated solver. In our experiments, we demonstrate that our motion generation algorithm computes consistent contact forces and joint trajectories for our humanoid robot. We also demonstrate the favorable time complexity due to our formulation and composition of the momentum equations.
71 citations
••
05 Dec 2011TL;DR: This work takes as an input a planned sequence of static postures that represent the contact configuration transitions; a multi-objective controller then synthesizes the motion between these postures, the objectives of the controller being decided by a finite-state machine.
Abstract: Our objective in this work is to synthesize dynamically consistent motion for a simulated humanoid robot in acyclic multi-contact locomotion using multi-objective control. We take as an input a planned sequence of static postures that represent the contact configuration transitions; a multi-objective controller then synthesizes the motion between these postures, the objectives of the controller being decided by a finite-state machine. Results of this approach are presented in the attached video in the form of playback motions generated through non-real-time constraint-based dynamic simulations.
71 citations
••
TL;DR: This study resorts to a novel approach through which the decision is made according to fuzzy Markov decision processes (FMDP), with regard to the pace, and the experimental results show the efficiency of the proposed method.
71 citations