Footstep Planning for Rapid Path Following in Humanoid Robots

2016 ◽  
Vol 13 (04) ◽  
pp. 1650013 ◽  
Author(s):  
Zhang Jiwen ◽  
Liu Li ◽  
Chen Ken
Keyword(s):  
Constraint Satisfaction Problem ◽  
Path Following ◽  
Humanoid Robots ◽  
Step Frequency ◽  
Moving Vehicle ◽  
Planning Framework ◽  
Backtrack Search ◽  
Motion Speed ◽  
Real Robot ◽  
Dynamics Simulations

Rapid path following is an important component of a layered planning framework to improve motion speed. A method of generating a bipedal footstep sequence that follows a designated path and maintains stability in a planar environment is proposed in this paper. It adopts a walking style with a fixed step frequency and adjusts consecutive strides by eliminating irrational stride changes. An omnidirectional moving vehicle model and the deduced inequalities are introduced to theoretically describe the inter-pace constraints. A modified backtrack search is then implemented to solve the resulting constraint satisfaction problem. Both dynamics simulations and real robot experiments show that a humanoid robot is capable of tracking various paths with rapid paces. Comparison with several alternatives verifies the superiority of this novel method in terms of rapidity.

Planning with Concurrency, Time and Resources

2005 ◽  
pp. 259-295 ◽  
Author(s):  
Amedeo Cesta ◽  
Simone Fratini ◽  
Angelo Oddi
Keyword(s):  
Constraint Satisfaction ◽  
Resource Availability ◽  
Constraint Satisfaction Problem ◽  
Satellite System ◽  
Domain Model ◽  
Planning Problem ◽  
Planning And Scheduling ◽  
Planning Framework ◽  
Current Implementation ◽  
Domain Description

This chapter proposes to model a planning problem (e.g., the control of a satellite system) by identifying a set of relevant components in the domain (e.g., communication channels, on-board memory or batteries), which need to be controlled to obtain a desired temporal behavior. The domain model is enriched with the description of relevant constraints with respect to possible concurrency, temporal limits and scarce resource availability. The paper proposes a planning framework based on this view that relies on a formalization of the problem as a Constraint Satisfaction Problem (CSP) and defines an algorithmic template in which the integration of planning and scheduling is a fundamental feature. In addition, the paper describes the current implementation of a constraint-based planner called OMP that is grounded on these ideas and shows the role constraints have in this planner, both at domain description level and as a guide for problem solving.

Footstep adaptation strategy for reactive omnidirectional walking in humanoid robots

Robotica ◽  
2017 ◽  
Vol 36 (1) ◽  
pp. 57-77 ◽  
Author(s):  
Jiwen Zhang ◽  
Zeyang Xia ◽  
Li Liu ◽  
Ken Chen
Keyword(s):  
Optimization Problem ◽  
Center Of Mass ◽  
Humanoid Robots ◽  
Adaptation Strategy ◽  
Vehicle Model ◽  
Risk Of Falling ◽  
Response Quality ◽  
Foot Placement ◽  
Planning Framework ◽  
Simulation Based

SUMMARYStability, high response quality and rapidity are required for reactive omnidirectional walking in humanoids. Early schemes focused on generating gaits for predefined footstep locations and suffered from the risk of falling over because they lacked the ability to suitably adapt foot placement. Later methods combining stride adaptation and center of mass (COM) trajectory modification experienced difficulties related to increasing computing loads and an unwanted bias from the desired commands. In this paper, a hierarchical planning framework is proposed in which the footstep adaption task is separated from that of COM trajectory generation. A novel omnidirectional vehicle model and the inequalities deduced therefrom are adopted to describe the inter-pace connection relationship. A constrained nonlinear optimization problem is formulated and solved based on these inequalities to generate the optimal strides. A black-box optimization problem is then constructed and solved to determine the model constants using a surrogate-model-based approach. A simulation-based verification of the method and its implementation on a physical robot with a strictly limited computing capacity are reported. The proposed method is found to offer improved response quality while maintaining rapidity and stability, to reduce the online computing load required for reactive walking and to eliminate unnecessary bias from walking intentions.

scholarly journals Planning Grasping Motions for Humanoid Robots

2019 ◽  
Vol 16 (06) ◽  
pp. 1950041 ◽  
Author(s):  
Jan Rosell ◽  
Raúl Suárez ◽  
Néstor García ◽  
Muhayy Ud Din
Keyword(s):  
Humanoid Robot ◽  
State Of The Art ◽  
Search Space ◽  
Humanoid Robots ◽  
Hand Motion ◽  
Everyday Objects ◽  
Human Movements ◽  
Family Types ◽  
Real Robot ◽  
Grasp Type

This paper addresses the problem of obtaining the required motions for a humanoid robot to perform grasp actions trying to mimic the coordinated hand–arm movements humans do. The first step is the data acquisition and analysis, which consists in capturing human movements while grasping several everyday objects (covering four possible grasp types), mapping them to the robot and computing the hand motion synergies for the pre-grasp and grasp phases (per grasp type). Then, the grasp and motion synthesis step is done, which consists in generating potential grasps for a given object using the four family types, and planning the motions using a bi-directional multi-goal sampling-based planner, which efficiently guides the motion planning following the synergies in a reduced search space, resulting in paths with human-like appearance. The approach has been tested in simulation, thoroughly compared with other state-of-the-art planning algorithms obtaining better results, and also implemented in a real robot.

scholarly journals Technique of Standing Up From Prone Position of a Soccer Robot

2018 ◽  
Vol 6 (1) ◽  
pp. 124-136 ◽  
Author(s):  
Nur Khamdi ◽  
Mochamad Susantok ◽  
Antony Darmawan
Keyword(s):  
Prone Position ◽  
Degrees Of Freedom ◽  
Humanoid Robot ◽  
Humanoid Robots ◽  
Soccer Robot ◽  
Robot Soccer ◽  
The Real ◽  
Limited Movement ◽  
Standing Up ◽  
Real Robot

One of the humanoid robots being developed in the field of sports is a soccer robot. A soccer robot is a humanoid robot that can perform activities such as playing football. And a variety method fall down of robot soccer such: falling down toward the front direction, side direction, and rear direction. This paper describes the most stands up methods of a soccer robot from its prone position. The proposed method requires only limited movement with degrees of freedom. The movement standing-up of soccer robot has been implemented on the real robot. Tests we performed showed that reliable standing-up from prone position is possible after a fall and such recovery procedures greatly improve the overall robustness of a Soccer Robot.

scholarly journals Provably constant-time planning and replanning for real-time grasping objects off a conveyor belt

2021 ◽  
pp. 027836492110271
Author(s):  
Fahad Islam ◽  
Oren Salzman ◽  
Aditya Agarwal ◽  
Maxim Likhachev
Keyword(s):  
Real Time ◽  
Conveyor Belt ◽  
Constant Time ◽  
Time Motion ◽  
Planning Framework ◽  
Perception System ◽  
Conveyor Belts ◽  
Real Robot ◽  
Time Planning ◽  
Manufacturing Environments

In warehouse and manufacturing environments, manipulation platforms are frequently deployed at conveyor belts to perform pick-and-place tasks. Because objects on the conveyor belts are moving, robots have limited time to pick them up. This brings the requirement for fast and reliable motion planners that could provide provable real-time planning guarantees, which the existing algorithms do not provide. In addition to the planning efficiency, the success of manipulation tasks relies heavily on the accuracy of the perception system which is often noisy, especially if the target objects are perceived from a distance. For fast-moving conveyor belts, the robot cannot wait for a perfect estimate before it starts executing its motion. In order to be able to reach the object in time, it must start moving early on (relying on the initial noisy estimates) and adjust its motion on-the-fly in response to the pose updates from perception. We propose a planning framework that meets these requirements by providing provable constant-time planning and replanning guarantees. To this end, we first introduce and formalize a new class of algorithms called constant-time motion planning (CTMP) algorithms that guarantee to plan in constant time and within a user-defined time bound. We then present our planning framework for grasping objects off a conveyor belt as an instance of the CTMP class of algorithms. We present it, provide its analytical properties, and perform an experimental analysis both in simulation and on a real robot.

scholarly journals A Reactive Strategy for High-Level Consistency During Search

2018 ◽  
Author(s):  
Robert J. Woodward ◽  
Berthe Y. Choueiry ◽  
Christian Bessiere
Keyword(s):  
Constraint Satisfaction Problem ◽  
Constraint Propagation ◽  
Search Tree ◽  
Benchmark Problems ◽  
Search Performance ◽  
Arc Consistency ◽  
Backtrack Search ◽  
Reactive Strategy ◽  
Active Research ◽  
High Level

Constraint propagation during backtrack search significantly improves the performance of solving a Constraint Satisfaction Problem. While Generalized Arc Consistency (GAC) is the most popular level of propagation, higher-level consistencies (HLC) are needed to solve difficult instances. Deciding to enforce an HLC instead of GAC remains the topic of active research. We propose a simple and effective strategy that reactively triggers an HLC by monitoring search performance: When search starts thrashing, we trigger an HLC, then conservatively revert to GAC. We detect thrashing by counting the number of backtracks at each level of the search tree and geometrically adjust the frequency of triggering an HLC based on its filtering effectiveness. We validate our approach on benchmark problems using Partition-One Arc-Consistency as an HLC. However, our strategy is generic and can be used with other higher-level consistency algorithms.

Bipedal Locomotion Control Based on Simultaneous Trajectory and Foot Step Planning

2016 ◽  
Vol 28 (4) ◽  
pp. 533-542 ◽  
Author(s):  
Kouta Goto ◽  
◽  
Yuichi Tazaki ◽  
Tatsuya Suzuki
Keyword(s):  
Constraint Satisfaction Problem ◽  
Center Of Mass ◽  
Bipedal Locomotion ◽  
Nonlinear Constraint ◽  
Inverted Pendulum Model ◽  
Pendulum Model ◽  
Lower Figure ◽  
Planning Methods ◽  
Real Robot ◽  
Trajectory Tracking Controller

[abstFig src='/00280004/11.jpg' width='300' text='Snapshots of a bipedal robot walking forward (upper figure) and walking sideways (lower figure)' ] This paper proposes a trajectory planner for bipedal locomotion that determines a center-of-mass (CoM) trajectory, footsteps, and step durations simultaneously. Trajectory planning based on a linear inverted pendulum model is formulated as a nonlinear constraint satisfaction problem. The proposed iterative constraint solving algorithm is able to solve this problem in a short amount of time so that trajectory replanning at every walking step is possible. Unlike existing planning methods that determine footsteps and a CoM trajectory sequentially under fixed walking period, the proposed planner can produce complex walking patterns that fully utilize the interdependency of these physical quantities. The proposed trajectory planner and a trajectory tracking controller is implemented on a real robot and their performance is evaluated.

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