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In this work, we present a per-instant pose optimization method that cangenerate configurations that achieve specified pose or motion objectives asbest as possible over a sequence of solutions, while also simultaneouslyavoiding collisions with static or dynamic obstacles in the environment. Wecast our method as a multi-objective, non-linear constrained optimization-basedIK problem where each term in the objective function encodes a particular poseobjective. We demonstrate how to effectively incorporate environment collisionavoidance as a single term in this multi-objective, optimization-based IKstructure, and provide solutions for how to spatially represent and organizeexternal environments such that data can be efficiently passed to a real-time,performance-critical optimization loop. We demonstrate the effectiveness of ourmethod by comparing it to various state-of-the-art methods in a testbed ofsimulation experiments and discuss the implications of our work based on ourresults.

CollisionIK: A Per-Instant Pose Optimization Method for Generating Robot Motions with Environment Collision Avoidance