6533b837fe1ef96bd12a3344
RESEARCH PRODUCT
An Optimized Architecture for CGA Operations and Its Application to a Simulated Robotic Arm
Salvatore VitabileSilvia FranchiniGiorgio Vassallosubject
conformal geometric algebraSettore ING-INF/05 - Sistemi Di Elaborazione Delle Informazioniapplication-specific processorsComputer Networks and CommunicationsHardware and ArchitectureControl and Systems EngineeringSignal Processingcomputational geometryFPGA-based prototypingElectrical and Electronic Engineeringapplication-specific processors; Clifford Algebra; computational geometry; conformal geometric algebra; FPGA-based prototyping; grasping; human-like robotic arms; inverse kinematicsdescription
Conformal geometric algebra (CGA) is a new geometric computation tool that is attracting growing attention in many research fields, such as computer graphics, robotics, and computer vision. Regarding the robotic applications, new approaches based on CGA have been proposed to efficiently solve problems as the inverse kinematics and grasping of a robotic arm. The hardware acceleration of CGA operations is required to meet real-time performance requirements in embedded robotic platforms. In this paper, we present a novel embedded coprocessor for accelerating CGA operations in robotic tasks. Two robotic algorithms, namely, inverse kinematics and grasping of a human-arm-like kinematics chain, are used to prove the effectiveness of the proposed approach. The coprocessor natively supports the entire set of CGA operations including both basic operations (products, sums/differences, and unary operations) and complex operations as rigid body motion operations (reflections, rotations, translations, and dilations). The coprocessor prototype is implemented on the Xilinx ML510 development platform as a complete system-on-chip (SoC), integrating both a PowerPC processing core and a CGA coprocessing core on the same Xilinx Virtex-5 FPGA chip. Experimental results show speedups of 78× and 246× for inverse kinematics and grasping algorithms, respectively, with respect to the execution on the PowerPC processor.
| year | journal | country | edition | language |
|---|---|---|---|---|
| 2022-10-28 |