1.4 -> 1.5, fix syntax

docs/overview.html

@@ -395,7 +395,7 @@ <h2> Contents </h2>
   <section id="overview">
 <h1>Overview<a class="headerlink" href="#overview" title="Link to this heading">#</a></h1>
 <p><img alt="gallery of_environments" src="images/gallery.png" /></p>
-<p><strong>robosuite</strong> is a simulation framework powered by the <a class="reference external" href="http://mujoco.org/">MuJoCo</a> physics engine for robot learning. It also offers a suite of benchmark environments for reproducible research. The current release (v1.4) features long-term support with the official MuJoCo binding from DeepMind. This project is part of the broader <a class="reference external" href="https://github.com/ARISE-Initiative">Advancing Robot Intelligence through Simulated Environments (ARISE) Initiative</a>, with the aim of lowering the barriers of entry for cutting-edge research at the intersection of AI and Robotics.</p>
+<p><strong>robosuite</strong> is a simulation framework powered by the <a class="reference external" href="http://mujoco.org/">MuJoCo</a> physics engine for robot learning. It also offers a suite of benchmark environments for reproducible research. The current release (v1.5) features diverse robot embodiments (including humanoids), custom robot composition, composite controllers (including whole body controllers), more teleoperation devices and photo-realistic rendering. This project is part of the broader <a class="reference external" href="https://github.com/ARISE-Initiative">Advancing Robot Intelligence through Simulated Environments (ARISE) Initiative</a>, with the aim of lowering the barriers of entry for cutting-edge research at the intersection of AI and Robotics.</p>
 <p>Data-driven algorithms, such as reinforcement learning and imitation learning, provide a powerful and generic tool in robotics. These learning paradigms, fueled by new advances in deep learning, have achieved some exciting successes in a variety of robot control problems. However, the challenges of reproducibility and the limited accessibility of robot hardware (especially during a pandemic) have impaired research progress. The overarching goal of <strong>robosuite</strong> is to provide researchers with:</p>
 <ul class="simple">
 <li><p>a standardized set of benchmarking tasks for rigorus evaluation and algorithm development;</p></li>

index.md

@@ -10,7 +10,7 @@ videoId: "robosuite-v1.5-video.mp4"
 ![pull figure]({{ 'assets/images/gallery_logo.jpg' | absolute_url }})
 
 **robosuite** is a simulation framework powered by the [MuJoCo](http://mujoco.org/) physics engine for robot learning. It also offers a suite of benchmark environments for reproducible research.
-The current release (v1.5) features diverse robot embodiments (including humanoids), custom robot composition, composite controllers (including whole body controllers), more teleoperation devices, photo-realistic rendering. 
+The current release (v1.5) features diverse robot embodiments (including humanoids), custom robot composition, composite controllers (including whole body controllers), more teleoperation devices and photo-realistic rendering. 
 This project is part of the broader [Advancing Robot Intelligence through Simulated Environments (ARISE) Initiative](https://github.com/ARISE-Initiative), with the aim of lowering the barriers of entry for cutting-edge research at the intersection of AI and Robotics.
 
 # New Releases