diff --git a/lerobot/common/datasets/aloha.py b/lerobot/common/datasets/aloha.py
index 7397327d..95a33450 100644
--- a/lerobot/common/datasets/aloha.py
+++ b/lerobot/common/datasets/aloha.py
@@ -73,11 +73,11 @@ def download(data_dir, dataset_id):
 
     data_dir.mkdir(parents=True, exist_ok=True)
 
-    gdown.download_folder(FOLDER_URLS[dataset_id], output=data_dir)
+    gdown.download_folder(FOLDER_URLS[dataset_id], output=str(data_dir))
 
     # because of the 50 files limit per directory, two files episode 48 and 49 were missing
-    gdown.download(EP48_URLS[dataset_id], output=data_dir / "episode_48.hdf5", fuzzy=True)
-    gdown.download(EP49_URLS[dataset_id], output=data_dir / "episode_49.hdf5", fuzzy=True)
+    gdown.download(EP48_URLS[dataset_id], output=str(data_dir / "episode_48.hdf5"), fuzzy=True)
+    gdown.download(EP49_URLS[dataset_id], output=str(data_dir / "episode_49.hdf5"), fuzzy=True)
 
 
 class AlohaExperienceReplay(AbstractExperienceReplay):
diff --git a/lerobot/common/envs/aloha/env.py b/lerobot/common/envs/aloha/env.py
index b9b13d66..d92c2f49 100644
--- a/lerobot/common/envs/aloha/env.py
+++ b/lerobot/common/envs/aloha/env.py
@@ -370,14 +370,10 @@ class AlohaEnv(EnvBase):
             raise NotImplementedError()
             # self._prev_action_queue = deque(maxlen=self.num_prev_action)
 
-    def render(self, mode="rgb_array", width=384, height=384):
-        if width != height:
-            raise NotImplementedError()
-        tmp = self._env.render_size
-        self._env.render_size = width
-        out = self._env.render(mode)
-        self._env.render_size = tmp
-        return out
+    def render(self, mode="rgb_array", width=640, height=480):
+        # TODO(rcadene): render and visualizer several cameras (e.g. angle, front_close)
+        image = self._env.physics.render(height=height, width=width, camera_id="top")
+        return image
 
     def _format_raw_obs(self, raw_obs):
         if self.from_pixels:
@@ -535,8 +531,10 @@ class AlohaEnv(EnvBase):
         # )
 
         # TODO(rcaene): add bounds (where are they????)
-        self.action_spec = UnboundedContinuousTensorSpec(
+        self.action_spec = BoundedTensorSpec(
             shape=(len(ACTIONS)),
+            low=-1,
+            high=1,
             dtype=torch.float32,
             device=self.device,
         )