ROAug 2, 2021

Redundancy Resolution in Kinematic Control of Serial Manipulators in Multi-Obstacle Environment

arXiv:2108.00762v1
Originality Synthesis-oriented
AI Analysis

This addresses motion planning for a novel manipulator type in cluttered environments, but it appears incremental as it applies known methods to a new robot design.

The paper tackled redundancy resolution for a new tensegrity-based serial manipulator in multi-obstacle environments by decomposing it into collision-free path planning for the end-effector using discrete dynamic programming and motion planning for the robot body using quadratic programming, with efficiency confirmed by simulation.

The paper focuses on the redundancy resolution in kinematic control of a new type of serial manipulator composed of multiple tensegrity segments, which are moving in a multi-obstacle environment. The general problem is decomposed into two sub-problems, which deal with collision-free path planning for the robot end-effector and collision-free motion planning for the robot body. The first of them is solved via discrete dynamic programming, the second one is worked out using quadratic programming with mixed linear equality/nonequality constraints. Efficiency of the proposed technique is confirmed by simulation.

Foundations

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