scholarly journals Comparison of kinematic and dynamic leg trajectory optimization techniques for biped robot locomotion

2017 ◽  
Vol 803 ◽  
pp. 012069 ◽  
Author(s):  
R Khusainov ◽  
A Klimchik ◽  
E Magid
2015 ◽  
Vol 35 (8) ◽  
pp. 1000-1019 ◽  
Author(s):  
Andrew D. Marchese ◽  
Russ Tedrake ◽  
Daniela Rus

The goal of this work is to develop a soft-robotic manipulation system that is capable of autonomous, dynamic, and safe interactions with humans and its environment. First, we develop a dynamic model for a multi-body fluidic elastomer manipulator that is composed entirely from soft rubber and subject to the self-loading effects of gravity. Then, we present a strategy for independently identifying all of the unknown components of the system; these are the soft manipulator, its distributed fluidic elastomer actuators, as well as the drive cylinders that supply fluid energy. Next, using this model and trajectory-optimization techniques we find locally-optimal open-loop policies that allow the system to perform dynamic maneuvers we call grabs. In 37 experimental trials with a physical prototype, we successfully perform a grab 92% of the time. Last, we introduce the idea of static bracing for a soft elastomer arm and discuss how forming environmental braces might be an effective manipulation strategy for this class of robots. By studying such an extreme example of a soft robot, we can begin to solve hard problems inhibiting the mainstream use of soft machines.


Author(s):  
M. Matsuura ◽  
K. Ishimura ◽  
S. Shimada ◽  
M. Wada
Keyword(s):  

Robotica ◽  
2000 ◽  
Vol 18 (2) ◽  
pp. 163-170 ◽  
Author(s):  
M.-Y. Cheng ◽  
C.-S. Lin

Most studies in the past on the control of biped locomotion considered only level surfaces. However, in the real world the ground is rarely completely flat. More research on locomotion on less structured surfaces is needed. In this study, we investigated a control design method that searches for suitable control and trajectory parameters using a Genetic Algorithm (GA). Many sets of parameters are generated through the search and the best set is selected based on a robustness measure developed from the linearized Poincaré map. This technique reduces tedious analysis and is favorably applicable to the design for locomotion on unstructured surfaces, for which analytical approaches are less appropriate. Simulations have been performed. Control parameters for different slopes were obtained and stored in a database. During the control, the control parameters suitable for the current surface slope were retrieved and the trajectory for a level surface was modified according to the surface slope. The control parameters changed values according to the terrain. Simulation results were promising.


2021 ◽  
Vol 8 ◽  
Author(s):  
Junhyeok Ahn ◽  
Steven Jens Jorgensen ◽  
Seung Hyeon Bang ◽  
Luis Sentis

We propose a locomotion framework for bipedal robots consisting of a new motion planning method, dubbed trajectory optimization for walking robots plus (TOWR+), and a new whole-body control method, dubbed implicit hierarchical whole-body controller (IHWBC). For versatility, we consider the use of a composite rigid body (CRB) model to optimize the robot’s walking behavior. The proposed CRB model considers the floating base dynamics while accounting for the effects of the heavy distal mass of humanoids using a pre-trained centroidal inertia network. TOWR+ leverages the phase-based parameterization of its precursor, TOWR, and optimizes for base and end-effectors motions, feet contact wrenches, as well as contact timing and locations without the need to solve a complementary problem or integer program. The use of IHWBC enforces unilateral contact constraints (i.e., non-slip and non-penetration constraints) and a task hierarchy through the cost function, relaxing contact constraints and providing an implicit hierarchy between tasks. This controller provides additional flexibility and smooth task and contact transitions as applied to our 10 degree-of-freedom, line-feet biped robot DRACO. In addition, we introduce a new open-source and light-weight software architecture, dubbed planning and control (PnC), that implements and combines TOWR+ and IHWBC. PnC provides modularity, versatility, and scalability so that the provided modules can be interchanged with other motion planners and whole-body controllers and tested in an end-to-end manner. In the experimental section, we first analyze the performance of TOWR+ using various bipeds. We then demonstrate balancing behaviors on the DRACO hardware using the proposed IHWBC method. Finally, we integrate TOWR+ and IHWBC and demonstrate step-and-stop behaviors on the DRACO hardware.


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