Abstract: In the field of mobile robotics, data is transmitted from the robot over low bandwidth channels or incrementally in short bursts to a host, where it can be further processed for visualization. JPEG-LS is the one of the image and file compressions, in which the Huffman decoding is used to compress the result of quantization stage. In the recent production and management scenario, advanced factories require first an increasing degree of automation to reduce the product cost and, second, availability of greater flexibility of output and product types. To meet such requirements in near future, the factories need to link the flow of material, energy and information together more efficiently. In order to link the flow of information with other entities, we have to involve data compression, coding and decoding techniques. The speed is very demanding for such applications which in turn motivate to develop a fast decoding algorithm to meet the challenges arising in the field of predicting collision free path for robot. Huffman decoding has been widely used in data, image and video compression. This motivates the present work. For a Concurrent Read and Exclusive Write (CREW), Parallel Random Access Machine (PRAM) model with N processors, we propose a parallel algorithm for Huffman decoding in this paper. The algorithm employs (N+1)-ary search, which is parallel version of binary search. Its time complexity amounts to O (log N+1 (n+1)), where n is the number of symbols in a Huffman tree.