Browsing by Subject "Footstep planning"

Now showing 1 - 4 of 4

Open Access
An approximate stance map of the spring mass hopper with gravity correction for nonsymmetric locomotions
(IEEE, 2009) Arslan, Ömür; Saranlı, Uluç; Morgül, Ömer
The Spring-Loaded Inverted Pendulum (SLIP) model has long been established as an effective and accurate descriptive model for running animals of widely differing sizes and morphologies, while also serving as a basis for several hopping robot designs. Further research on this model led to the discovery of several analytic approximations to its normally nonintegrable dynamics. However, these approximations mostly focus on steady-state running with symmetric trajectories due to their linearization of gravitational effects, an assumption that is quickly violated for locomotion on more complex terrain wherein transient, non-symmetric trajectories dominate. In this paper, we introduce a novel gravity correction scheme that extends on one of the more recent analytic approximations to the SLIP dynamics and achieves good accuracy even for highly non-symmetric trajectories. Our approach is based on incorporating the total effect of gravity on the angular momentum throughout a single stance phase and allows us to preserve the analytic simplicity of the approximation to support our longer term research on reactive footstep planning for dynamic legged locomotion. We compare the performance of our method in simulation to two other existing analytic approximations and show that it outperforms them for most physically realistic non-symmetric SLIP trajectories while maintaining the same accuracy for symmetric trajectories. © 2009 IEEE.
Open Access
A new footstep planning for SLIP and TD-SLIP models
(2020-12) İslamoğlu, Serkan
Spring Loaded Inverted Pendulum (SLIP) is a well-known model and an accurate descriptive tool, which can scientifically represent the dynamics of the legged locomotion. Torque actuated Dissipative SLIP (TD-SLIP), on the other hand, is fundamentally an enhanced version of the SLIP model. Inclusion of more realistic damping model and the hip torque actuation has led the researchers to develop a sufficiently better analytic approximation. This thesis proposes a new methodology to achieve footstep planning on the SLIP and TD-SLIP models, distinctly. It contributes a novel planning algorithm by utilising the constructed touchdown-totouchdown map, and a novel recursive function to plan and execute the planning. The thesis provides a background information about the modelling and simulation of both of the used models, and an auxiliary function, which administers a derivative-free method to calculate the minimum of an input function. After defining the problems and the corresponding proposed solutions, the foundations of the preparation phase is established. This phase is fundamentally constructed to accumulate required information for the algorithm implementation and simulation phase. The main phase consists of subsections, which can be composed of the combination of following properties; planning type, as online and offline, policy type; as forward and backwards and output type; as based on distance or based on minimum step count. According to the stated problem, the planning is successfully realised not only for a single desired distance, but also an array of waypoints. In addition to this, the presented illustrations of different initial states show that the planning can also be constructed via any different initial touchdown state. Therefore, the obtained results are quite promising, since all of the cases and their combinations successfully reach the destinations with a negligible error value, which is less than 1%. Although, the offline planning type provides the results in a rapid way, the obtained data to use the plan requires much more space, which also increases dramatically when the step count (level) is incremented. In addition to this, the forward planning is faster than the backwards one, but they both generate very similar results.
Open Access
Reactive footstep planning for a planar spring mass hopper
(IEEE, 2009-10) Arslan, Ömür; Saranlı, Uluç; Morgül, Ömer
The main driving force behind research on legged robots has always been their potential for high performance locomotion on rough terrain and the outdoors. Nevertheless, most existing control algorithms for such robots either make rigid assumptions about their environments (e.g flat ground), or rely on kinematic planning at low speeds. Moreover, the traditional separation of planning from control often has negative impact on the robustness of the system against model uncertainty and environment noise. In this paper, we introduce a new method for dynamic, fully reactive footstep planning for a simplified planar spring-mass hopper, a frequently used model for running behaviors. Our approach is based on a careful characterization of the model dynamics and an associated deadbeat controller, used within a sequential composition framework. This yields a purely reactive controller with a very large, nearly global domain of attraction that requires no explicit replanning during execution. Finally, we use a simplified hopper in simulation to illustrate the performance of the planner under different rough terrain scenarios and show that it is extremely robust to both model uncertainty and measurement noise. © 2009 IEEE.
Open Access
Reactive planning and control of planar spring-mass running on rough terrain
(Institute of Electrical and Electronics Engineers, 2012) Arslan, Ö.; Saranlı, U.
An important motivation for work on legged robots has always been their potential for high-performance locomotion on rough terrain. Nevertheless, most existing control algorithms for such robots either make rigid assumptions about their environments or rely on kinematic planning at low speeds. Moreover, the traditional separation of planning from control often has negative impact on the robustness of the system. In this paper, we introduce a new method for dynamic, fully reactive footstep planning for a planar spring-mass hopper, based on a careful characterization of the model dynamics and the design of an associated deadbeat controller, used within a sequential composition framework. This yields a purely reactive controller with a large domain of attraction that requires no explicit replanning during execution. We show in simulation that plans constructed for a simplified dynamic model can successfully control locomotion of a more complete model across rough terrain. We also characterize the performance of the planner over rough terrain and show that it is robust against both model uncertainty and measurement noise without replanning. © 2012 IEEE.