Planning collision-free reaching motions for interactive object manipulation and grasping

Abstract

We present new techniques that use motion planning algorithms based on probabilistic roadmaps to control 22 degrees of freedom (DOFs) of human-like characters in interactive applications. Our main purpose is the automatic synthesis of collision-free reaching motions for both arms, with automatic column control and leg flexion. Generated motions are collision-free, in equilibrium, and respect articulation range limits. In order to deal with the high (22) dimension of our configuration space, we bias the random distribution of configurations to favor postures most useful for reaching and grasping. In addition, extensions are presented in order to interactively generate object manipulation sequences: a probabilistic inverse kinematics solver for proposing goal postures matching pre-designed grasps; dynamic update of roadmaps when obstacles change position; online planning of object location transfer; and an automatic stepping control to enlarge the character's reachable space. This is, to our knowledge, the first time probabilistic planning techniques are used to automatically generate collision-free reaching motions involving the entire body of a human-like character at interactive frame rates. Categories and Subject Descriptors(according to ACM CCS): I.3.7 [Computer Graphics]: Three-Dimensional Graphics and Realism † Work done while at EPFL -Virtual Reality Lab nity. Most of the techniques developed 1 have not sufficiently explored this domain.The automatic generation of collision-free grasping sequences has several direct applications in virtual reality, games, and computer animation. And yet, producing collision-free grasping motions currently involves lots of tedious manual work from designers.Motion planning originated in Robotics, with an emphasis on the synthesis of collision-free motions for any sort of robotic structure 2 . Some works have applied mo-

An Energy-Driven Motion Planning Method for Two Distant Postures

“…Kallmann et al [8] propose a Probabilistic Roadmap-based planning algorithm to synthesize reaching and grasping motion while assuming prior knowledge about the motion. Pan et al [9] propose an efficient method to plan the motion in constrained environment by classifying body parts into groups with low-correlation.…”

A Fast Motion Planning Approach for Virtual Human Upper Body

“…If there's no new collision-free configuration q new that either locates outside of the inactive regions, or satisfies the distance descending condition: e(q new ) < e goal , no further step toward goal regions is permitted in current loop, and the node q near in T is pushed into InactiveRegion list to prevent it from being chosen as an candidate extending configuration in the next iteration. Otherwise, q new is added to the branch of T by a straight-line edge, and the minimum distance error e goal is updated (line [5][6][7][8][9][10][11][12][13][14]. The collision detection relies on the PQP package from the University of North Carolina [15].…”

“…Kuffner et al [5] presented bi-directional RRT-Connect approach to design collision-free motion of virtual human arm. Kallmann et al [6] proposed a biased RRT algorithm to account for manipulation tasks in dynamic environments. Yamane et al [7] combined the greedy RRT with the motion capture data to generate natural manipulation motion.…”

Development of a configuration space motion planner for robot in dynamic environment

“…To further reduce the execution time so as to make them applicable in changing environments, these methods need to re-build the roadmap or adapt the roadmap to the environmental changes. As examples, in [19,20], roadmaps are maintained in the dynamic environment, i.e., all nodes that become invalid after an obstacle change are deleted. Nevertheless, new configurations have to be sampled again to fill the empty regions created, which is a time-costly procedure.…”