IPAB Workshop - 09/05/2019

Iordanis Chatzinikolaidis

Title: Dynamic footstep planning for legged robots using trajectory optimization

Abstract: Footstep planning for legged robots is a challenging task; for one, due to the hybrid nature of the models considered. Most successful approaches rely on simplified linear models with prespecified contacts. As a result, the computed motions correspond to a very restricted domain of a robot's capabilities, while a priori specifying contacts can be non-intuitive. Trajectory optimization methods are commonly used for planning locally optimal trajectories for robotic systems but handling models with contact is not straightforward. In this talk, we will present an overview of these methods, how they are related to classical complementarity methods for resolving contacts, and how we formulate our approach along with relevant results.

Wolfgang Merkt

Title: Continuous-Time Collision Avoidance for Trajectory Optimization in Dynamic Environments

Abstract:

Common formulations to consider collision avoidance in trajectory optimization often use either preprocessed environments or only check and penalize collisions at discrete time steps.

However, when only checking at discrete states, this requires either large margins that prevent manipulation close to obstacles or dense time discretization increasing the dimensionality of the optimization problem in complex environments. Nonetheless, collisions may still occur in the interpolation/transition between two valid states or in environments with thin obstacles.

In this work, we introduce a computationally inexpensive continuous-time collision avoidance term in presence of static and moving obstacles. Our penalty is based on conservative advancement and harmonic potential fields and can be used as either a cost or constraint in off-the-shelf nonlinear programming solvers.

Due to the use of conservative advancement (collision checks) rather than distance computations, our method outperforms discrete collision avoidance based on signed distance constraints resulting in smooth motions with continuous-time safety while planning in discrete time.

We evaluate our proposed continuous collision avoidance on scenarios including manipulation of moving targets, locomanipulation on mobile robots, manipulation trajectories for humanoids, and quadrotor path planning and  compare penalty terms based on harmonic potential fields with ones derived from contact normals.