Steve Tonneau

A Reachability-Based Planner for Sequences of Acyclic Contacts in Cluttered Environments

Multiped locomotion in cluttered environments is addressed as the problem of planning acyclic sequences of contacts, that characterize the motion. In order to overcome the inherent combinatorial difficulty of this problem, we separate it in two subproblems: first, planning a guide trajectory for the root of the robot and then, generating relevant contacts along this trajectory. This paper proposes theoretical contributions to these two subproblems. We propose a theoretical characterization of the guide trajectory, named “true feasibility”, which guarantees that a guide can be mapped into the contact manifold of the robot. As opposed to previous approaches, this property makes it possible to assert the relevance of a guide trajectory without explicitly computing contact configurations. Indeed, this property is efficiently checked using a low dimensional sampling-based planner (e.g. we implemented a visibility PRM). Since the guide trajectories that we characterize are easily mapped into a valid sequence of contacts, we then focus on how to select a particular sequence with desirable properties, such as robustness, efficiency and naturalness, only considered in cyclic locomotion so far. Based on these novel theoretical developments, we implement a complete acyclic contact planner and demonstrate its efficiency by producing a large variety of motions with three very different robots (humanoid, insectoid, dexterous hand) in five challenging scenarios. The quality of the obtained motions and the performance of the algorithm make it the first acyclic contact planner suitable for interactive applications.

Using task efficient contact configurations to animate creatures in arbitrary environments

A common issue in three-dimensional animation is the creation of contacts between a virtual creature and the environment. Contacts allow force exertion, which produces motion. This paper addresses the problem of computing contact configurations allowing to perform motion tasks such as getting up from a sofa, pushing an object or climbing. We propose a two-step method to generate contact configurations suitable for such tasks. The first step is an offline sampling of the range of motion (ROM) of a virtual creature. The ROM of the human arms and legs is precisely determined experimentally. The second step is a run time request confronting the samples with the current environment. The best contact configurations are then selected according to a heuristic for task efficiency. The heuristic is inspired by the force transmission ratio. Given a contact configuration, it measures the potential force that can be exerted in a given direction. The contact configurations are then used as inputs for an inverse kinematics solver that will compute the final animation. Our method is automatic and does not require examples or motion capture data. It is suitable for real time applications and applies to arbitrary creatures in arbitrary environments. Various scenarios (such as climbing, crawling, getting up, pushing or pulling objects) are used to demonstrate that our method enhances motion autonomy and interactivity in constrained environments. Graphical abstractA method for the realtime computation of contact configurations for arbitrary creatures and environments is proposed, using a heuristic for task efficiency.Display Omitted HighlightsWe automatically compute limb contact configurations for animating motion tasks.The quality of the configurations is ensured by a heuristic for task efficiency.We obtain real time performances for arbitrary creatures and environments.A precise definition of the human range of motion enhances more natural results.

Dynamically balanced and plausible trajectory planning for human-like characters

We present an interactive motion planning algorithm to compute plausible trajectories for high-DOF human-like characters. Given a discrete sequence of contact configurations, we use a three-phase optimization approach to ensure that the resulting trajectory is collision-free, smooth, and satisfies dynamic balancing constraints. Our approach can directly compute dynamically balanced and natural-looking motions at interactive frame rates and is considerably faster than prior methods. We highlight its performance on complex human motion benchmarks corresponding to walking, climbing, crawling, and crouching, where the discrete configurations are generated from a kinematic planner or extracted from motion capture datasets.

Zero Step Capturability for Legged Robots in Multicontact

The ability to anticipate a fall is fundamental for any robot that has to balance. Currently, fast fall-prediction algorithms only exist for simple models, such as the linear inverted pendulum model (LIPM), whose validity breaks down in multicontact scenarios (i.e., when contacts are not limited to a flat ground). This paper presents a fast fall-prediction algorithm based on the point-mass model, which remains valid in multicontact scenarios. The key assumption of our algorithm is that, in order to come to a stop without changing its contacts, a robot only needs to accelerate its center of mass in the direction opposite to its velocity. This assumption allows us to predict the fall by means of a convex optimal control problem, which we solve with a fast custom algorithm (less than 11 ms of computation time). We validated the approach through extensive simulations with the humanoid robot HRP-2 in randomly-sampled scenarios. Comparisons with standard LIPM-based methods demonstrate the superiority of our algorithm in predicting the fall of the robot, when controlled with a state-of-the-art balance controller. This paper lays the foundations for the solution of the challenging problem of push recovery in multicontact scenarios.

2PAC: Two Point Attractors for Center of Mass Trajectories in Multi Contact Scenarios

Synthesizing motions for legged characters in arbitrary environments is a long-standing problem that has recently received a lot of attention from the computer graphics community. We tackle this problem with a procedural approach that is generic, fully automatic, and independent from motion capture data. The main contribution of this article is a point-mass-model-based method to synthesize Center Of Mass trajectories. These trajectories are then used to generate the whole-body motion of the character. The use of a point mass model results in physically inconsistent motions and joint limit violations when mapped back to a full- body motion. We mitigate these issues through the use of a novel formulation of the kinematic constraints that allows us to generate a quasi-static Center Of Mass trajectory in a way that is both user-friendly and computationally efficient. We also show that the quasi-static constraint can be relaxed to generate motions usable for computer animation at the cost of a moderate violation of the dynamic constraints. Our method was integrated in our open-source contact planner and tested with different scenarios—some never addressed before—featuring legged characters performing non-gaited motions in cluttered environments. The computational efficiency of our trajectory generation algorithm (under one ms to compute one second of trajectory) enables us to synthesize motions in a few seconds, one order of magnitude faster than state-of-the-art methods. Although our method is empirically able to synthesize collision-free motions, the formal handling of environmental constraints is not part of the proposed method and left for future work.

Character contact re-positioning under large environment deformation

Character animation based on motion capture provides intrinsically plausible results, but lacks the flexibility of procedural methods. Motion editing methods partially address this limitation by adapting the animation to small deformations of the environment. We extend one such method, the so‐called relationship descriptors, to tackle the issue of motion editing under large environment deformations. Large deformations often result in joint limits violation, loss of balance, or collisions. Our method handles these situations by automatically detecting and re‐positioning invalidated contacts. The new contact configurations are chosen to preserve the mechanical properties of the original contacts in order to provide plausible support phases. When it is not possible to find an equivalent contact, a procedural animation is generated and blended with the original motion. Thanks to an optimization scheme, the resulting motions are continuous and preserve the style of the reference motions. The method is fully interactive and enables the motion to be adapted on‐line even in case of large changes of the environment. We demonstrate our method on several challenging scenarios, proving its immediate application to 3D animation softwares and video games.